Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2017  |  Volume : 30  |  Issue : 3  |  Page : 637-644

Review on personalized colorectal cancer

Department of Internal Medicine, Faculty of Medicine, Jazan University, Jazan, Kingdom of Saudi Arabia

Date of Submission29-Dec-2015
Date of Acceptance29-Jan-2016
Date of Web Publication15-Nov-2017

Correspondence Address:
MD Hussein Ageely
2349 Almarjan Industrial Zone Rd, Unit No 1, Jazan 82621-7413
Kingdom of Saudi Arabia
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1110-2098.218285

Rights and Permissions

The aim of this work was to study biomarkers as indicators of personalization of medicine (PM) for colorectal cancer (CRC).
PM is considered to be the medicine of the future, as the scope of interest has shifted to patient-specific treatments and remedies. The understanding of human genomics improves the capability of better understanding diseases from the genetic perspective, which is particularly useful in treating CRC. Biomarkers are considered indicators that help in evaluating the prognosis of CRC; in fact, they are now considered to be reliable indices for the diagnosis and leveling of the different stages of cancer.
The author performed a narrative synthesis of studies for biomarkers in personalization of CRC. Therefore, relevant publications were identified, reference lists were examined, and citation searches were performed. No restrictions on date or type of study were applied.
Recent findings
Biomarkers are actively engaged in managing PM of CRC, as determined for diagnosis, follow-up, and progress of the treatment and also to select the appropriate treatment.
It would be recommended to use these biomarkers in clinical practice worldwide. Nevertheless, challenges arise in the implementation of biomarkers as diagnostic and prognostic tools because logistical and infrastructural improvements are needed.

Keywords: biomarkers, colorectal cancer, personalized medicine

How to cite this article:
Ageely H. Review on personalized colorectal cancer. Menoufia Med J 2017;30:637-44

How to cite this URL:
Ageely H. Review on personalized colorectal cancer. Menoufia Med J [serial online] 2017 [cited 2020 Apr 5];30:637-44. Available from: http://www.mmj.eg.net/text.asp?2017/30/3/637/218285

  Introduction Top

Advancement of medicine is to ensure specificity and selectivity: specificity to approach certain disease and selectivity to approach the selected patient. Hereby, the term personalization of medicine (PM) comes up, which means tailoring therapy and attuning to the individual patient, therefore making it highly effective. PM is a dynamic process of management starting from screening and diagnosis of diseases to eventually treating the patient. The patient therapy is categorized according to disease characteristics. PM is paving the way for the future to achieve success in the area of targeted therapy [1].

The concept of personalized medicine has been founded recently; nevertheless, selectivity and specificity have always been characteristics of medicine since the last century. On completion of the human genomic mapping in 2004, the flood of information regarding 22 000–23 000 mapped genes triggered the advances of medicine to establish valuable tools [2]. PM will benefit patients, communities, and pharmaceutical companies for better therapeutic management of patient diagnoses and treatments.

The advances of screening and diagnosis of disease mandate the development of biomarkers. These biomarkers will not only be useful to screen and diagnose diseases but they will also be used to evaluate the outcome and the progress of therapy.

Recently, PM has been used for many different diseases – for example, dermatologic, cardiovascular, and neurological, among many others. As malignancies have markedly increased in the past century, an increasing number of diseases have affected a large group of individuals, especially those living in cosmopolitan areas. Therefore, the need of PM in treating malignancies is justified and needed for patient screening, early diagnosis, and evaluating the progression of therapies [3].

Among the diseases of interest in applying the concept of PM is colorectal cancer (CRC). Determining the molecular profile of colon and rectal cancers offers the possibility of personalized cancer treatment. Genes and their products are involved in the biological pathways of human cancers; they can also be used as targets of new therapies, or predictive markers for the sensitivity and/or resistance to these therapies.


The aim of this work was to study biomarkers as indicators of PM for CRC.

  Methods Top

The author accomplished a narrative review to identify relevant publications through computerized searches of the databases from 1984 to 2015 of PubMed and Jazan digital library through manual searches. Reference lists were examined and citation searches were carried out. No restrictions on date or study type were applied. The data capture started from early detection of biomarkers of colorectal malignancy to the study of molecular pathology and epidemiology of CRC, generating a master table relating the identified biomarkers to CRC.

Molecular pathology and epidemiology of colorectal cancer

Over the past years, many studies were concerned with the treatment of CRC. The outcome depends on the personalization of this malignancy, which depends on the profile of individual patients. In addition to genetic and immunological predisposition, microbial inflammation is an important factor for cancer transformation of benign colon lesions.

The management of CRC depends on the screening and treatment either by surgery or chemotherapy. Despite the advances of the management, CRC is considered the first leading cause of death in Saudi Arabia.

As a basic role, carcinogenesis depends on two active steps of initiation and promotion. The initiation is not exclusively of genetic origin, but it can also be induced by bacterial drivers [4] or bovine virus [5]. The fermentation of undigested food remnants by bacteria is a perfect inducer for carcinogenic transformation of colon stem cells. Therefore, a diet rich in short-chain fatty acid or produced by bacterial fermentation is considered a high-risk diet, whereas a low-fat diet with high fermentable fibers is considered a low-CRC-risk diet [6]. Hence, lifestyle is strongly correlated with the development of CRC.

Different mechanisms have been associated with the development of CRC; these mechanisms are supported by the molecular pathology and epidemiological studies. Diet and luminal contents [7], tobacco smoking [8], and alcohol [9] are risk factors for the development of CRC. Bacterial inflammation initiated the carcinogenic transformation through the N-nitroso compounds [10], which produces an insult to DNA. A byproduct of inflammation is the formation of arachidonic acid and its metabolite prostaglandin E2 [11]. Prostaglandin E2 is the promoting factor for angiogenesis, suppressing immune system and induction of proliferation [12]. Aspirin, an irreversible COX inhibitor, is considered a mainstay in the prevention of CRC development [13],[14].

The genetic and molecular biology of CRC has been established, as the mucosal cells are proliferating, and in response to the luminal factors changes in epigenetics (changes of methylation and protein) can induce an insult to DNA transcription without genetic mutation [15]. The DNA repair system identifies and corrects the replication errors through tumor suppressor gene p53 (the guardian of the genome) [16]. Generally, the chromosomal instability pathway is famous for the accumulation of mutation of CRC via key genes – for example, Kras (BRAF/V600E), adenoma polyposis coli gene, and P53 [16],[17],[18],[19].

Role of biomarkers in personalization of medicine of colorectal cancer

The increase of knowledge in the field of molecular genetics has led to the identification of specific alterations present in the malignant evolution. Many of these have been proposed as biomarkers, which are of potential use in estimating CRC prognosis. Recently, there has been an impressive increase in the number of putative biomarkers that are capable of predicting the response to specific adjuvant treatment; however, it is not clear whether or not these putative biomarkers have prognostic value or therapeutic implications. They may well be useful in taking decisions regarding the prognosis of CRC patients, but further prospective trials are clearly required [20]. Identifying and understanding molecular markers can improve the effectiveness of treatment in several ways; for example, it can lead to the development of marker-specific therapies. Prognostic markers may also improve the selection of adjuvant therapies by identifying those who will benefit most and therefore avoid the toxic side effects of treatment in patients with the least risk for recurrence [20]. For now, predictive markers remain an open question, but clearly they will have a more important role to play in the future [Table 1].
Table 1: Established biomarkers and their therapeutic significance

Click here to view

Oncology is nowadays in a situation in which the huge stowage of data information on different levels of the neoplastic process requires their correlation and coherent fitting, in order to provide explanations and satisfying solutions with regard to taking adequate therapeutic decisions [1]. This situation might be described as a puzzle in which each piece from the large array available is still searching for its corresponding place in building the final picture. An approach in terms of prognostic and predictive factors is a valuable conceptual acquisition, which may clarify and open new directions in the avalanche of knowledge that defines CRC.

NIH classification of biomarkers [56]

The NIH acknowledges the value of biomarkers and classifies them into three categories:

  • Type 0: Markers of the natural history of a disease, which correlate longitudinally as clinical indices, such as symptoms
  • Type I: Markers that capture the effect of intervention based on the mechanism of action of the drugs
  • Type II: Markers that are associated with surrogate endpoints, as changes of these markers predict clinical benefits that are relevant to the mode of drug action and the pathophysiology of the disease.

Prognostic and predictive biomarkers

Prognostic factor is defined as any parameter evaluated at diagnosis (or surgery) that is associated with treatment outcome (disease free interval, survival, local control).

Predictive factor is any parameter that evaluates the response or lack of response to a specific treatment.

Summarizing the previously presented data, we would like to highlight the biological markers that have, at present, captured scientists' attention as prospective predictive factors in CRC:

  • Cellular proliferation indices are in research today both in relation to the Ki-67 protein, which blocks proliferation, and to proliferating cell nuclear antigen, the former being excellently correlated with the 'growth fraction', and the latter can only be expressed by proliferating cells, being directly connected to the 'aggressiveness' of the neoplastic process
  • Serum markers have been considered as great hope both as early diagnosis means, possibly for screening, and as prognostic factors. The CEA antigen, despite its lack of specificity, remains a useful prognostic factor in colonic cancer. Thus, its plasmatic levels should be restored to their normal values in a matter of 4–6 weeks after a radical resection. A19–9 has proved itself to be a specific marker in the development of CRC metastases. Its postoperative decrease has not been correlated with survival rates, and the screening of CA19–9 has not so far improved CRC patient management
  • T-cell infiltration is an adequate good prognosis indicator in CRC, considering that these lymphocytes are part of an immune response of the host to the aggressiveness of the tumor
  • Biochemical markers: Thymidylate synthase has been suggested as a prognostic and survival factor in CRC, as well as of the tumor cell response to 5-fluororacil therapy, meaning that its elevated levels are associated with resistance to this type of chemotherapy
  • Oncogenes: The p53 suppressor gene is still in research, most studies being in search of a correlation between the p53 protein and the apoptotic index
  • The RAS (K-ras, H-ras, and N- ras) family of oncogenes, located on the 12p chromosome, codifies the 21-kD proteins involved in both the cell proliferation and differentiation. The anomalies of this gene complex, which are present in tumor cells, can be connected to the high relapse and low survival rates
  • The MMR system deficiency is responsible for the microsatellite instability phenomenon, associated with a better prognosis in all CRC stages. Research of the factors involved in tumor cell invasion and metastasis, such as matrix metalloproteinase, has demonstrated their direct correlation with metastatic aggressiveness and potential, and their inhibitors have proven their efficiency in preclinical trials
  • Vascular endothelial growth factor is certainly associated with an unfavorable prognosis, whereas its predictive role in connection to the available drugs has not yet been demonstrated
  • Circulating tumor cells have proven themselves to be an independent prognostic factor, meaning that their presence in the blood stream appears to be an early marker for recurrence and relapse.

Prognostic markers can improve patient selection for a given treatment, avoiding toxic side effects in patients, which are not included in the benefit group.

Prediction markers remain a subject of interest and debate of antitumor agent selection research.

Clinical relevancy of biomarkers in cancer colon

Biomarkers are paving the road for better management of CRC and also other malignancies. Upon completing the meta-analysis for the different types of cancers and biomarkers, clinical decisions will be selective and specific. The specificity will be in choosing the most effective protocol of treatment and selectivity for follow-up and prognosis. The biomarkers also help to locate the site of malignancy: KRAS tumor markers progressively decreased from sigmoid to transverse (all P < 0.0001). KRAS level changes when CRC spreads to the lumen [57]. Nevertheless, the KRAS provides independent prognostic information [41]. The newly discovered biomarker (miR-320e) is indicative to the staging of the cancer colon; its expression was significantly elevated in stage III colon cancers from patients with recurrence compared with patients without recurrence (95% confidence interval = 1.14–1.42; P < 0.0001) [58], and also independently validated in stage II and III tumors, as well as in the staging of malignancy [58].

Development of biomarkers is a must for the prevention and prognostic evaluation of a cancer-free zone. The initial stages of clinical evaluation for any biomarker must rely on dose titration to identify the optimal range, and for evidence that the agent is hitting its intended target (s) and having the desired downstream effects. The ultimate issue is how can we consider that biomarkers and its related products are pharmacologically active compounds for cancer treatment. The biomarkers may be indicators of a process or a mechanism of action – for example, apoptosis or cell proliferation or more specific measures at a molecular or biochemical level. Preclinical data include convincing evidence from in vivo models that biomarker changes correlate with efficacy.

Biomarkers may be generic indicators of a process such as apoptosis or cell proliferation or more specific measures at a molecular or biochemical level relating to a known (or anticipated) mechanism of action. In both cases, there should be convincing preclinical data, including evidence from an appropriate in-vivo model that biomarker changes correlate with efficacy. This new modality requires preintervention and postintervention biopsies for the evaluation of malignancies. Presurgical trials present a powerful tool to study the effect of biomarkers at the target tissue [59]. This approach has been successfully deployed in a variety of trials across several solid malignancies [60]. Short-term lapatinib (lapatinib is a tyrosine kinase inhibitor that targets human epidermal growth factor receptors [61]) given before surgery was found to decrease cell proliferation, as quantified by Ki-67 labeling index. Lapatinib affects HER-2-positive breast cancer tissue and premalignant ductal intraepithelial neoplasia, supporting further exploration of this drug for breast cancer prevention in high-risk patients [62].

Pharmacologically active concentrations of curcumin, a constituent of turmeric, were shown to reach the colorectum of patients who took 3.6 g daily during the week leading up to surgery. Activity was reflected by a significant reduction in the levels of a DNA damage marker of oxidative stress in malignant tissue after curcumin therapy [63].

However, it may be difficult to directly compare the measurement of some biomarkers in preintervention biopsy samples with postintervention surgical tissues taken from the same patient. Technical differences in the procedure may influence biomarker levels, and there is a potential for sampling errors because of the small amounts of tissue available at biopsy [64]. Therefore, these possibilities emphasize the importance of incorporating a placebo or a control group into biomarker trials to fully appreciate the influence of procedural and technical factors.

Until now, there are fewer reports demonstrating the successful analysis and modulation of a specific target or pathway in tissue after intervention [65],[66],[67]. This technique is in a process of maturation in the next few years where therapeutic biomarkers will be mechanism-targeted compounds (drugs). The analysis of epigenetic changes, particularly genome-wide DNA methylation patterns, is receiving considerable attention for the discovery of tissue and blood-based biomarkers of cancer risk and also as indicators of biological activity or efficacy of preventive interventions [68],[69]. Recently, the use of aspirin has been associated with modulation of age and cancer-related DNA methylation changes in normal colonic epithelium of women, suggesting that it can affect the evolution of cancer methylomes [69].

Challenges facing personalization of medicine in colorectal cancer [70]

The pitfalls in measuring biomarkers must also be pointed out, and standardized sample treatment must be ensured so that comparable results are obtained. Moreover, the half-lives of most markers have not yet been defined precisely. The problem of specificity or allocation of biomarkers to their respective malignant diseases was alluded to above. The list of unanswered questions on the topic of PM in the context of screening is certainly a long one. Nevertheless, PM in the area of screening is promising and to date has been used too little.

  Conclusion Top

It would be recommended to use these biomarkers in clinical practice worldwide to diagnose and manage CRC. These biomarkers are the gate of the future, which will shape medicine and personalize the diseases. Nevertheless, biomarkers are facing a lot of challenges to serve the concept of PM. These challenges are the requirement of the following: a biospecimen from every patient, a validated assay run in a CLIA (Clinical Laboratory Improvement Amendment)-certified laboratory with acceptable turnaround time, a drug that hits the target, a regulatory system willing to approve drugs and companion diagnostics with greater flexibility, reimbursement and regulatory incentives to develop molecular diagnostics, a drug industry willing to trade widespread short-term drug use for chronic therapy in more limited populations, family physicians who are experts in genomic medicine, and, most importantly, doctors and patients who are willing and able to participate in clinical trials [57].

A question that arises is 'Can personalized medicine modality be applied to every society and every country worldwide?' The answer to this question is convoluted as the application of PM will need certain prerequisites as challenges are bound to arise. Nevertheless, challenges arise in the implementation of biomarkers as diagnostic and prognostic tools because logistical and infrastructural improvements are needed.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Schmalfuss F, Kolominsky-Rabas PL. Personalized medicine in screening for malignant disease: a review of methods and applications. Biomark Insights 2013; 8:9–14.  Back to cited text no. 1
Schmutz J, Wheeler J, Grimwood, J, Dickson M, Yang J, Caoile C, et al. Quality assessment of the human genome sequence. Nature 2004; 429:365–368.  Back to cited text no. 2
Pokorska-Bocci A, Stewart A, Sagoo GS, Hall A, Kroese M, Burton H'. Personalized medicine: what's in a name?. Pers Med 2014; 11:197–210.  Back to cited text no. 3
Rampelli S, Schnorr SL, Consolandi C, Turroni S, Severgnini M, Peano C. Sequencing of the Hadza hunter-gatherer gut microbiota. Curr Biol 2015; 25:1682–1693.  Back to cited text no. 4
Zur Hausen H. Red meat consumption and cancer: reasons to suspect involvement of bovine infectious factors in colorectal cancer. Int J Cancer 2012; 130:2475–2483.  Back to cited text no. 5
Fung KY, Ooi CC, Zucker MH, Lockett T, Williams DB, Cosgrove LJ, et al. Colorectal carcinogenesis: a cellular response to sustained risk environment. Int J Mol Sci 2013; 14:13525–13541.  Back to cited text no. 6
Leonel AJ, Alvarez-Leite JI. Butyrate: implications for intestinal function. Curr Opin Clin Nutr Metab Care 2012; 15:474–479.  Back to cited text no. 7
Jensen K, Afroze S, Munshi MK, Guerrier M, Glaser SS. Mechanisms for nicotine in the development and progression of gastrointestinal cancers. Transl Gastrointest Cancer 2012; 1:81–87.  Back to cited text no. 8
Moskal A, Norat T, Ferrari P, Riboli E. Alcohol intake and colorectal cancer risk: a dose–response meta-analysis of published cohort studies. Int J Cancer 2007; 120:664–671.  Back to cited text no. 9
Lu H, Ulanov AV, Nobu M, Liu WT. Global metabolomic responses of Nitrosomonas europaea 19718 to cold stressand altered ammonia feeding patterns. Appl Microbiol Biotechnol 2015; 100:1843–52.  Back to cited text no. 10
Jones MK, Wang H, Peskar BM, Levin E, Itani RM, Sarfeh IJ, et al. Inhibition of angiogenesis by nonsteroidal anti-inflammatory drugs: insight into mechanisms and implications for cancer growth and ulcer healing. Nat Med 1999; 5:1418–1423.  Back to cited text no. 11
Berstad P, Thiis-Evensen E, Vatn MH, Almendingen K. Fatty acids in habitual diet, plasma phospholipids, and tumour and normal colonic biopsies in young colorectal cancer patients. J Oncol 2012; 2012:254801.  Back to cited text no. 12
Cathcart MC, Lysaght J, Pidgeon GP. Eicosanoid signalling pathways in the development and progression of colorectal cancer: novel approaches for prevention/intervention. Cancer Metastasis Rev 2011; 30:363–385.  Back to cited text no. 13
Nolfo F, Rametta S, Marventano S, Grosso G, Mistretta A, Drago F, et al. Pharmacological and dietary prevention for colorectal cancer. BMC Surg 2013; 13 (Suppl 2):S16.  Back to cited text no. 14
Spilianakis CG, Lalioti MD, Town T, Lee GR, Flavell RA. Interchromosomal associations between alternatively expressed loci. Nature 2005; 435:637–645.  Back to cited text no. 15
Richardson RB. p53 mutations associated with aging-related rise in cancer incidence rates. Cell Cycle 2013; 12:2468–2478.  Back to cited text no. 16
Dobre M, Comănescu M, Arsene D, Iosif C, Bussolati G. K-ras gene mutation status in colorectal cancer: comparative analysis of pyrosequencing and PCR-RFLP. Rom J Morphol Embryol 2013; 54:567–574.  Back to cited text no. 17
Bond CE, Nancarrow DJ, Wockner LF, Wallace L, Montgomery GW, Leggett BA, et al. Microsatellite stable colorectal cancers stratified by the BRAF V600E mutation show distinct patterns of chromosomal instability. PLoS One. 2014; 9:e91739.  Back to cited text no. 18
Alberici P, Fodde R. The role of the APC tumor suppressor in chromosomal instability. Genome Dyn 2006; 1:149–170.  Back to cited text no. 19
Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med 2010; 363:301–304.  Back to cited text no. 20
Isola JJ, Helin HJ, Helle MJ, Kallioniemi OP. Evaluation of cell proliferation in breast carcinoma. Comparison of Ki-67 immunohistochemical study, DNA flow cytometric analysis, and mitotic count. Cancer 1990;65:1180–1184.  Back to cited text no. 21
Eminović-Behrem S, Trobonjaca Z, Petrovecki M, Dobi-Babić R, Dujmović M, Jonjić N. Prognostic significance of DNA ploidy pattern and nucleolar organizer regions (AgNOR) in colorectal carcinoma. Croat Med J 2000; 41:154–158.  Back to cited text no. 22
Bravo R, Frank R, Blundell PA, Macdonald-Bravo H. Cyclin/PCNA is the auxiliary protein of DNA polymerase delta. Nature 1987; 326:515–517.  Back to cited text no. 23
Levine AJ. p53, the cellular gatekeeper for growth and division. Cell 1997; 88:323–331.  Back to cited text no. 24
Sigal A, Rotter V. Oncogenic mutations of the p53 tumor suppressor: the demons of the guardian of the genome. Cancer Res 2000; 60:6788–6793.  Back to cited text no. 25
Benchimol S, Fuks A, Jothy S, Beauchemin N, Shirota K, Stanners CP. Carcinoembryonic antigen, a human tumor marker, functions as an intercellular adhesion molecule. Cell 1989; 57:327–334.  Back to cited text no. 26
Fletcher RH. Carcinoembryonic antigen. Ann Intern Med 1986; 104:66–73.  Back to cited text no. 27
Ilantzis C, DeMarte L, Screaton RA, Stanners CP. Deregulated expression of the human tumor marker CEA and CEA family member CEACAM6 disrupts tissue architecture and blocks colonocyte differentiation. Neoplasia 2002; 4:151–163.  Back to cited text no. 28
Miura M, Ichikawa Y, Tanaka K, Kamiyama M, Hamaguchi Y, Ishikawa T, et al. Real-time PCR (TaqMan PCR) quantification of carcinoembryonic antigen (CEA) mRNA in the peripheral blood of colorectal cancer patients. Anticancer Res 2003; 23:1271–1276.  Back to cited text no. 29
Ritts REJr, Del Villano BC, Go VL, Herberman RB, Klug TL, Zurawski VRJr. Initial clinical evaluation of an immunoradiometric assay for CA 19-9 using the NCI serum bank. Int J Cancer 1984; 33:339–345.  Back to cited text no. 30
Gupta MK, Arciaga R, Bocci L, Tubbs R, Bukowski R, Deodhar SD. Measurement of a monoclonal-antibody-defined antigen (CA19-9) in the sera of patients with malignant and nonmalignant diseases. Comparison with carcinoembryonic antigen. Cancer 1985; 56:277–283.  Back to cited text no. 31
Thomas WM, Robertson JF, Price MR, Hardcastle JD. Failure of CA19-9 to detect asymptomatic colorectal carcinoma. Br J Cancer 1991; 63:975–976.  Back to cited text no. 32
Dieci MV, Criscitiello C, Goubar A, Viale G, Conte P, Guarneri V. Prognostic value of tumor-infiltrating lymphocytes on residual disease after primary chemotherapy for triple-negative breast cancer: a retrospective multicenter study. Ann Oncol 2014; 25:611–618.  Back to cited text no. 33
Yamachika T, Nakanishi H, Inada K, Tsukamoto T, Kato T, Fukushim M, et al. Anew prognostic factor for colorectalcarcinoma, thymidylate synthase, and its therapeutic significance. Cancer 1998; 82:70–77.  Back to cited text no. 34
Edler D, Hallstrom M, Johnston PG, Magnusson I, Ragnhammar P, Blomgren H. Thymidylate synthase expression: an independent prognostic factor for local recurrence, distant metastasis, disease-free and overall survival in rectal cancer. Clin Cancer Res 2000; 6:1378–1384.  Back to cited text no. 35
Ion D, Stoian RV, Păduraru DN, Bolocan A, Serban MB. Certitudes and controversy regarding neural elements preservation in total mesorectal excision technique (ETM). Chirurgia (Bucur) 2012; 107:231–236.  Back to cited text no. 36
Vogelstein B, Fearon ER, Hamilton SR, Kern SE, Preisinger AC, Leppert M Nakamura Y, et al. Genetic alterations during colorectaltumor development. N Engl J Med 1988; 319:525–532.  Back to cited text no. 37
Paradiso A, Simone G, Petroni S, Leone B, Vallejo C, Lacava J, et al. Thymidilate synthase and p53 primary tumour expression as predictive factors for advanced colorectal cancer patients. Br J Cancer 2000; 82:560–567.  Back to cited text no. 38
Nastase A, Pâslaru L, Niculescu AM, Ionescu M, Dumitraşcu T, Herlea V. et al. Prognostic and predictive potential molecular biomarkers in colon cancer. Chirurgia (Bucur) 2011; 106:177–185.  Back to cited text no. 39
Popescu NC, Amsbaugh SC, DiPaolo JA, Tronick SR, Aaronson SA, Swan DC. Chromosomal localization of three human ras genes by in situ molecular hybridization. Somat Cell Mol Genet 1985;11:149–155.  Back to cited text no. 40
Pajkos G, Kiss I, Sلndor J, Ember I, Kishلzi P. The prognostic value of the presence of mutations at the codons 12, 13, 61 of K-ras oncogene in colorectal cancer. Anticancer Res 2000; 20:1695–1701.  Back to cited text no. 41
Bolocan A, Ion D, Stoian RV, Serban MB. HNPCC syndrome (hereditary non polypoid colorectal cancer) under-diagnosed or neglected pathology. Arch Balkan Med Union 2010; 45:245–249.  Back to cited text no. 42
Mureşan F, Simescu R, Domşa I, Buiga R, Cazacu M. Immunohistochemical screening of hMLH1 and hMSH2 gene mutations in patients diagnosed with colorectal cancer and microsatellite instability suspicion. Chirurgia (Bucur) 2011; 106:775–780.  Back to cited text no. 43
Halford S, Sasieni P, Rowan A, Wasan H, Bodmer W, Talbot I, et al. Low-level microsatellite instability occurs in most colorectal cancers and is a nonrandomly distributed quantitative trait. Cancer Res 2002; 62:53–57.  Back to cited text no. 44
Poon RT, Fan ST, Wong J. Clinical implications of circulating angiogenic factors in cancer patients. J Clin Oncol 2001; 19:1207–1225.  Back to cited text no. 45
Minagawa N, Nakayama Y, Hirata K, Onitsuka K, Inoue Y, Nagata N, Itoh H. Correlation of plasma level and immunohistochemical expression of vascular endothelial growth factor in patients with advanced colorectal cancer. Anticancer Res 2002; 22:2957–2963.  Back to cited text no. 46
Kumar H, Heer K, Duthie GS, Monson JR. Kinetics of postoperative serum vascular endothelial growth factor (VEGF) – Can it be used to predict curative resections in colorectal cancer? Anticancer Res 2002; 22:3717–3722.  Back to cited text no. 47
Cassano A, Bagala C, Battelli C, Schinzari G, Quirino M, Ratto C, et al. Expression of vascular endothelial growth factor, mitogen-activated protein kinase and p53 in human colorectal cancer. Anticancer Res 2002; 22:2179–2184.  Back to cited text no. 48
Kumar H, Heer K, Greenman J, Kerin MJ, Monson JR. Soluble FLT-1 is detectable in the sera of colorectal and breast cancer patients. Anticancer Res 2002;22:1877–1880.  Back to cited text no. 49
Coussens LM, Werb Z. Matrix metalloproteinases and the development of cancer. Chem Biol 1996; 3:895–904.  Back to cited text no. 50
Nagase H, Woessner JFJr. Matrix metalloproteinases. J Biol Chem 1999; 274:21491–21494.  Back to cited text no. 51
Kahari VM, Saarialho-Kere U. Matrix metalloproteinases and their inhibitors in tumour growth and invasion. Ann Med 1999; 31:34–45.  Back to cited text no. 52
Kerkela E, Ala-aho R, Klemi P, Grenman S, Shapiro SD, Kahari VM, et al. Metalloelastase (MMP-12) expression by tumour cells in squamous cell carcinoma of the vulva correlates with invasiveness, while that by macrophages predicts better outcome. J Pathol 2002; 198:258–269.  Back to cited text no. 53
Lukyanchuk VV, Friess H, Kleeff J, Osinsky SP, Ayuni E, Candinas D, Roggo A. Detection of circulating tumor cells by cytokeratin 20 and prostate stem cell antigen RT-PCR in blood of patients with gastrointestinal cancers. Anticancer Res 2003; 23:2711–2716.  Back to cited text no. 54
Albuquerque AD, Kubisch I, Stölzel U, Ernst D, Boese-Landgraf J, Breier G, et al. Prognostic and predictive value of circulating tumor cell analysis in colorectal cancer patients. J Transl Med 2012; 10:222.  Back to cited text no. 55
Jr Atkinson AJ, Colburn WA, DeGruttola VG, DeMets DL, Downing GJ, Hoth DF, et al. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferreddefinitions and conceptual framework. Clin Pharmacol Ther 2001; 69:89–95.  Back to cited text no. 56
Sinicrope FA, Mahoney MR, Yoon HH, Smyrk TC, Thibodeau SN, Goldberg RM, et al. Analysis of molecular markers by anatomic tumor site in stage III colon carcinomas from adjuvant chemotherapy. Clin Cancer Res 2015; 21:5294–5304.  Back to cited text no. 57
Perez-Carbonell L, Sinicrope FA, Alberts SR, Oberg AL, Balaguer F, Castells A, et al. MiR-320e is a novel prognostic biomarker in colorectal cancer. Br J Cancer 2015; 113:83–90.  Back to cited text no. 58
Kalinsky K, Hershman DL. Cracking open window of 'opportunity trials. J Clin Oncol 2012; 30:2573–2575.  Back to cited text no. 59
Kummar S, Doroshow JH. Phase 0 trials: expediting the development of chemoprevention agents. Cancer Prev Res (Phila) 2011; 4:288–292.  Back to cited text no. 60
Paul B, Trovato JA, Thompson J. Lapatinib: a dual tyrosine kinase inhibitor for metastatic breast cancer. Am J Health Syst Pharm 2008; 65:1703–1710.  Back to cited text no. 61
Decensi A, Puntoni M, Pruneri G, Guerrieri-Gonzaga A, Lazzeroni M, Serrano D, et al. Lapatinib activityin premalignant lesions and HER-2-positive cancer of the breast in a randomized, placebo-controlled presurgical trial. Cancer Prev Res 2011; 4:1181–1189.  Back to cited text no. 62
Garcea G, Berry DP, Jones DJ, Singh R, Dennison AR, Farmer PB, et al. Consumption of the putative chemopreventive agent curcumin by cancer patients: assessment of curcumin levels in the colorectum and their pharmacodynamic consequences. Cancer Epidemiol Biomarkers Prev 2005; 14:120–125.  Back to cited text no. 63
Cazzaniga M, DeCensi A, Pruneri G, Puntoni M, Bottiglieri L, Varricchio C, et al. The effect of metformin on apoptosis in a breast cancer presurgical trial. Br J Cancer 2013; 109:2792–2797.  Back to cited text no. 64
Boyle JO, Meyskens FLJr, Garewal HS, Gerner EW. Polyamine contents in rectal and buccal mucosae in humans treated with oral difluoromethylornithine. Cancer Epidemiol Biomarkers Prev 1992; 1:131–135.  Back to cited text no. 65
Patel KR, Brown VA, Jones DJ, Britton RG, Hemingway D, Miller AS, et al. Clinical pharmacology of resveratrol and its metabolites in colorectal cancer patients. Cancer Res 2010; 70:7392–7399.  Back to cited text no. 66
Smith IE, Dowsett M, Ebbs SR, Dixon JM, Skene A, Blohmer JU, et al. Neoadjuvant treatment of postmenopausal breast cancer with anastrozole, tamoxifen, or both in combination: the Immediate Preoperative Anastrozole, Tamoxifen, or Combined with Tamoxifen (IMPACT) multicenter double-blind randomized trial. J Clin Oncol 2005; 23:5108–5116.  Back to cited text no. 67
Brennan K, Flanagan JM. Is there a link between genome-wide hypomethylation in blood and cancer risk? Cancer Prev Res (Phila) 2012; 5:1345–1357.  Back to cited text no. 68
Noreen F, Röösli M, Gaj P, Pietrzak J, Weis S, Urfer P, et al. Modulation of age- and cancer-associated DNA methylation change in the healthy colon by aspirin and lifestyle. J Natl Cancer Inst 2014; 106(7).  Back to cited text no. 69
Malaney P, Nicosia SV, Davé V. One mouse, one patient paradigm: new avatars of personalized cancer therapy. Cancer Letters 2014; 344:1–12.  Back to cited text no. 70


  [Table 1]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Article Tables

 Article Access Statistics
    PDF Downloaded227    
    Comments [Add]    

Recommend this journal