Tumour biomarkers: homeostasis as a novel - Open Biology

Tumour biomarkers: homeostasis as a novel - Open Biology

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018 Tumour biomarkers: homeostasis as a novel prognostic indicator rsob.royalsoc...

446KB Sizes 0 Downloads 5 Views

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

Tumour biomarkers: homeostasis as a novel prognostic indicator rsob.royalsocietypublishing.org

Review Cite this article: Falco M et al. 2016 Tumour biomarkers: homeostasis as a novel prognostic indicator. Open Biol. 6: 160254. http://dx.doi.org/10.1098/rsob.160254

Received: 8 September 2016 Accepted: 10 November 2016

Subject Area: biochemistry/molecular biology/biophysics/ genomics/systems biology Keywords: homeostasis, cancer, biomarkers, metabolomics

Author for correspondence: Claudio Arra e-mail: [email protected]

Michela Falco1,†, Giuseppe Palma1,†, Domenica Rea1, Davide De Biase6, Stefania Scala2, Massimiliano D’Aiuto3, Gaetano Facchini4, Sisto Perdona`5, Antonio Barbieri1 and Claudio Arra1 1

Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori ‘Fondazione G. Pascale’, IRCCS, Via Mariano Semmola, 80131 Naples, Italy 2 Molecular lmmunology and Immuneregulation, Istituto Nazionale per lo Studio e la Cura dei Tumori, IRCCS Naples ‘Fondazione G. Pascale’, Naples, italy, Istituto Nazionale Tumori ‘Fondazione G. Pascale’, IRCCS, Via Mariano Semmola, 80131 Naples, Italy 3 Division of Breast Surgery, Department of Breast Disease, National Cancer Institute, IRCCS, ‘Fondazione Pascale’, Naples, Italy 4 Division of Medical Oncology, Department of Uro-Gynaecological Oncology, and 5Department of Urology, Istituto Nazionale per lo Studio e la Cura dei Tumori ‘Fondazione G. Pascale’, IRCCS, 80131 Naples, Italy 6 Department of Veterinary Medicine and Animal Production, University of Naples ‘Federico II’, Via Delpino 1, 80137 Naples, Italy CA, 0000-0003-3162-2091 The term ‘personalized medicine’ refers to a medical procedure that consists in the grouping of patients based on their predicted individual response to therapy or risk of disease. In oncologic patients, a ‘tailored’ therapeutic approach may potentially improve their survival and well-being by not only reducing the tumour, but also enhancing therapeutic response and minimizing the adverse effects. Diagnostic tests are often used to select appropriate and optimal therapies that rely both on patient genome and other molecular/cellular analysis. Several studies have shown that lifestyle and environmental factors can influence the epigenome and that epigenetic events may be involved in carcinogenesis. Thus, in addition to traditional biomarkers, epigenetic factors are raising considerable interest, because they could potentially be used as an excellent tool for cancer diagnosis and prognosis. In this review, we summarize the role of conventional cancer genetic biomarkers and their association with epigenomics. Furthermore, we will focus on the so-called ‘homeostatic biomarkers’ that result from the physiological response to cancer, emphasizing the concept that an altered ‘new’ homeostasis influence not only tumour environment, but also the whole organism.

1. Introduction

These authors contributed equally to this study.

The last decade has seen significant advances in the development of biomarkers in oncology; they play a critical role in understanding molecular and cellular mechanisms which drive tumour initiation, maintenance and progression. A cancer biomarker refers to a substance or process that is indicative for the presence of tumour in the body and therefore it may be a molecule secreted by the tumour or a specific body response to it [1]. Genetic, epigenetic, proteomic and imaging biomarkers can be used for cancer diagnosis, prognosis and epidemiology, and some of them can be assayed in organic fluids like blood or serum [2]. While numerous challenges exist in translating biomarker research into the clinic, a number of genes and protein-based biomarkers have already been used for patient diagnosis and care, including BRCA1/BRCA2 (breastrelated cancer antigens), BRAF-V600E (melanoma/colorectal cancer), CA-125 (cancer antigen in ovarian cancer), CA19.9 (cancer antigen in pancreatic

& 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

Table 1. Predictive and prognostic oncological biomarkers of solid tumours.




gene abnormality

drug therapy

biological role of biomarker

EGFR K-ras G13D

over-expression gene mutation

imatinib cetuximab

signalling protein downstream of primary target

B-raf V600E DPD no mutated gene

gene mutation none

panitumumab tamoxifen

primary target


gene deletion/absence of expression

aromatase inhibitor

drug metabolism

BRCA1/2 HER2/neu (Erb-B2)

mutation or deletion gene amplification

olaparib trastuzumab

predictive and prognostic biomarkers


over-expression gene mutation

gefitinib erlotinib

DNA repair downstream of primary target

K-ras PSA

gene mutation over-expression

platinum biological enzalutamide

blocking testosterone


gene mutation

cancer), CEA (carcinoembryonic antigen in colorectal cancer), EGFR (epidermal growth factor receptor in non-small cell lung carcinoma), HER-2 (human epidermal receptor in breast cancer), PSA ( prostate-specific antigen in prostate cancer) and many others [3– 6]. Several biomarkers may be used not only to screen for primary tumour or patients prognosis, but also for monitoring status of disease, recurrence and response to therapy [7]. Currently, cancer biomarker research is rapidly growing to elucidate the molecular pathways for inter-individual differences in drug response. Recent technologies and their application, in the field of cancer therapy, have enabled identification of genetic variations that may predict patient response to chemotherapy and targeted therapies [8,9]. These genetic variations, together with epigenetic alteration (like DNA methylation and chromatin/histone modifications), can contribute to develop some new biomarkers [10,11].

2. Biomarkers in cancer Tumour biomarkers are substances present in or produced by a tumour or by the microenvironment in response to tumorigenesis or progression processes. They can be virtually used in early cancer diagnosis, anti-cancer therapy development, monitoring of treatment responses and detecting individual risk for cancer development; for example, a woman that, during a screening, shows to be carrier of a germline mutation, such as BRCA1, has an increased risk of developing breast/ovarian cancer [12,13]. They can be used also to obtain other important information about the various aspects of the relationship between cancer and patient. Cancer biomarkers allow predicting the response to therapy, by evaluating the probable benefits of a particular treatment selected on the basis of the clinical information given by the biomarkers. In this way, the choice of the appropriate treatment leads to the development of increasingly personalized anti-cancer therapies [14] (table 1). There are several distinct types of tumour biomarker based on different tumour aspects: genetics, epigenetics, proteomics, metabolomics and imaging technology.

3. Colorectal cancer Colorectal carcinoma (CRC) is the most common cancer of the gastrointestinal tract and the second most frequently diagnosed malignancy in adults [15]. Treatments used for CRC may include some combination of surgery, radiation therapy, chemotherapy and targeted therapy. Most recently, biologic agents such as cetuximab/panitumumab (monoclonal antibodies directed against the epidermal growth factor receptor, EGFR) and bevacizumab (a humanized monoclonal antibody that targets vascular endothelial growth factor) have been proven to have therapeutic benefits in CRC alone or in association with standard chemotherapy [16]. Randomized controlled trials (RCTs) have shown that colon screening is associated with a reduction in CRC mortality. In fact, some screening detects cancer at an early stage, when treatment is less arduous and more often results in cure, while other screening has the ability to detect adenomas as well as cancer [17]. CRC is a disease in which pathogenesis is influenced by genetic and epigenetic events that occur with tumour initiation and progression. Any biomarkers that have been identified can be used to predict clinical outcome beyond staging, and to inform treatment selection [18]. The improvements in early detection, thanks to the screening and the use of prognostic biomarkers, have led to a decline in the incidence rate of colon cancer for the past 2 years [17]. In clinical routine biomarkers [19] such as EGFR gene expression, K-ras G13D gene mutation, BRAF-V600E gene mutation are considered for therapy (table 2).

4. Clinical biomarkers in colorectal cancer 4.1. Human epidermal growth factor receptor 2 Human epidermal growth factor receptor 2 (HER2) is a member of the EGFR family, having tyrosine kinase activity. Approximately 70% of human colorectal cancers express EGFR protein. Receptor dimerization results in the autophosphorylation of tyrosine residues within the cytoplasmic domains of the two receptors, and in the initiation of a variety

Open Biol. 6: 160254


predictive biomarker




Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

Table 2. Genetic biomarkers in colorectal cancer patients. therapy


anti-EGFR monoclonal antibody


cetuximab and panitumumab monoclonal antibody

4.2. K-ras (G13D gene mutation) K-ras, a member of RAS proto-oncogenes family, is the most frequently mutated gene in all human cancer and particularly it is an important oncogene in CRC. The K-ras protein is a downstream effector of EGFR that signals, through BRAF, the mitogen-activated protein kinase (MAPK) pathway activation and promotes cell growth and survival [22]. Mutations in K-ras codons 12 or 13 occur in approximately 40% of colorectal cancers and lead to constitutive signalling by impairing the ability of GTPase activating proteins to hydrolyse K-rasbound GTP; these mutations cause resistance to cetuximab and panitumumab [23]. Recently, published RCTs have established the use of K-ras mutational analysis as a predictive marker for anti-EGFR mAb resistance in patients with metastatic colorectal cancer [24,25].

4.3. BRAF (V600E gene mutation) Currently, BRAF mutations are found in 35– 45% of colorectal cancers and they are considered to be a prognostic biomarker for poor prognosis in patients receiving first-line colon cancer therapies [26]. The biological evidence for BRAF-V600E mutations employment as an additional biomarker of antiEGFR mAb resistance is strong: (i) BRAF is the immediate downstream effector of K-ras in the Ras/Raf/MAPK signalling pathway and (ii) BRAF-V600E activating mutations are 100% mutually exclusive of K-ras mutations in colorectal cancer, implying that the activation of either protein is sufficient for colon tumorigenesis. Previous studies support the use of BRAF-V600E as a negative predictor of response to anti-EGFR mAb therapy, leading to the evolving use of BRAF mutation testing in K-ras/wt patients [27]. This is considered to be an emerging biomarker of negative response to K-ras [28].

5. Epigenetic biomarkers in colorectal cancer CRC occurs in most cases as a result of both mutations and epigenetic modifications accumulated in several genes, particularly DNA mismatch repair genes, which cause the progression of disease from early adenoma to carcinoma and eventually to metastatic disease. In CRC, the hyper- or hypo-

molecular subtype



hormone receptor

Ki67 index hormone receptor


expression loss of ER positivity HER2þ

loss of HER2

monoclonal antibody

triple negative

gain of ER positivity gene mutations

CMF or CEF adjuvant chemotherapy

methylation events have been observed at each histological step from the polyps to adenocarcinoma [29]. Hyper-methylation events on CpG islands affect virtually all signalling pathways, including those of TP53, TGFb/ SMAD, WNT, NOTCH and tyrosine kinase receptors as well as those involved in cell cycle and transcription regulation, DNA stability, apoptosis, cell-to-cell adhesion, angiogenesis, invasion and metastasis [30,31]. Conversely, hypo-methylation, characterized by the gradual and complete depletion of methylated cytosine bases (5-methyl-cytosine) in cancer cells, is observed even in early stages of CRC until its development and progression [32]. Many studies have investigated the potential role of expression genes for prognostic use, and unsurprisingly most of them are similar to those with a high potential for diagnostic use; in example, promoter CpG methylation of HLTF and CDKN2A is used with prognostic and diagnostic functions in tumours [33,34]. More recent studies have revealed additional epigenetic biomarkers linked to CRC staging and progression. Methylation levels of genomic repeats, such as long interspersed nuclear element (LINE-1), have been recognized as independent factors for increased cancer-related mortality. LINE-1 hypo-methylation constitutes a potentially important feature of early onset CRC, and suggests a distinct molecular subtype [35]. Early onset of CRC represents a clinically distinct form of CRC that is often associated with a poor prognosis. LINE-1 enhanced activation through hypomethylation is associated with increased genomic instability and enhanced cancer ability to penetrate surrounding tissues and metastasize [36,37].

6. Breast cancer Breast cancer (BC), the most common cancer among women, is a heterogeneous and complex disease, whose precise progression mechanisms are less understood [38]. The molecular subgroups, also known as intrinsic subtypes of BC, have been defined by gene expression profiles, and they have distinct clinical features, metastatic behaviour, prognosis and treatment [39]. Despite the subtype identification, interand intratumour heterogeneity remain the principal causes of the marked differences observed in patients’ response to therapy and their prognosis [40] (table 3). Neo-adjuvant therapy (NAT) has become one of the standard treatments of patients with locally advanced BC; it

Open Biol. 6: 160254

of signalling pathways leading to cell proliferation and tumorigenesis. Therapies directed against HER2 have revolutionized the treatment of HER2 overexpressing CRC and gastric cancers, and they have improved their clinical outcome. AntiEGFR monoclonal antibodies (mAb), such as cetuximab and panitumumab, competitively inhibit EGFR by preventing its binding to endogenous ligands [20,21].




Table 3. Clinical biomarkers for breast cancer.

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

7.1. Oestrogen receptor and progesterone receptor gene expression The status of a BC is routinely identified by immunohistochemistry through identification of both predictive and prognostic biomarkers [43]. ER-positive status has the best predictive value for DFS [44], whereas PR-positive status indicates the presence of a functionally intact oestrogen response pathway, but it has primarily a prognostic and not predictive value compared with pharmacological treatment with tamoxifen. Moreover, high expressions of eR and PR are predictive for benefit from hormonal therapy in adjuvant treatment in patients with metastatic disease (Stage VII disease). Current clinical guidelines suggest that hormonal therapy is recommended for all patients with ER-positive disease regardless of their level of ER [45,46], even if not all ER-positive metastatic BCs respond to it. Recently, some reports have shown a genomic index for sensitivity to hormonal therapy based on genes associated with ESR1 (DNA copy of the ER) [47].

7.2. HER2 (Erb-B2)

9. Lung cancer

HER2 is a gene overexpressed or amplified in 15– 30% of invasive BCs, and it has both prognostic and predictive implications with a reduced survival [44]. HER2-positive tumours show an over-expression of HER2 protein, which has a predictive value compared to therapeutic treatment in patients of newly diagnosed BC. Moreover, over-expression of HER2 protein also shows a favourable response in patients treated with Trastuzumab, a monoclonal antibody that targets and blocks HER2 receptor, improving progression free survival and disease control. Oppositely, HER2-negative tumours do not respond to Trastuzumab [48,49]. In addition, there is new evidence that BC patients with HER2-positive tumours often benefit from Topoisomerase II (encoded by TOP2A gene) inhibitor-based chemotherapy such as doxorubicin or epirubicin [45].

Lung cancer (LC) is the most common reason of cancer deaths and [58,59] about 85% of LCs are non-small cell lung cancers (NSCLCs), traditionally divided into three major cell types: adenocarcinoma (50%), squamous cell carcinoma (35%) and large cell carcinoma (15%). The overall 5-year survival rate for LC has risen only 4% (from 12 to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving LC prognosis [60]. The most common symptoms are coughing (including coughing up blood), weight loss, shortness of breath and chest pains [61]. The presence of biomarkers in the plasma of patients with LC has aroused great clinical interest, since, with a simple blood test, a valid biomarker could be used for screening, diagnosis, prognosis, progression assessment and monitoring of therapeutic response [62]. A number of diagnostic biomarkers for LC have been suggested [63], including carcino-embryonic antigen, neuron-specific enolase, Cytokeratin 19 (CYFRA21.1), alpha-feto protein, serum carbohydrate antigen-125 (CA-125), carbohydrate antigen-19.9 (CA-19.9) and ferritin. These biomarkers have varied sensitivities for different subtypes of LC [64,65]. The major advance in the treatment of NSCLC developed from the recognition that specific genetic alterations define subsets of NSCLC; these subsets are characterized by genetic and

8. Epigenetic modifications as biomarkers in breast cancer Genetic and epigenetic alterations can control cancer induction and progression. Epigenetics refers to alterations in gene expression due to modifications in histone acetylation (HDAC) and DNA methylation of the promoter regions of


Open Biol. 6: 160254

7. Clinical biomarkers in breast cancer

genes. In BC biopsy specimens, HDAC-1 is associated with ER and PR expression; its gene expression levels gain during the earlier stage of neoplasia, representing a good marker of improved DFS [50]. HDAC-6 messenger RNA (mRNA) is more frequently expressed in ER- and PR-positive BC patients with small lesions (less than 2 cm) and low aggressiveness grade. However, different analyses failed to confirm that HDAC-6 expression is an independent prognostic factor for survival [50]. In BC, CpG island methylations of gene promoter regions play a major role in regulation of gene expression involved in a large spectrum of biological processes. Aberrant DNA hypo- or hyper-methylation should be useful as prognostic or diagnostic markers. DNA methylation in RASSF1A, DCR2APC and PTEN genes is observed in snap-frozen primary breast tumour associated with different stages of BC progression [51]. Therefore, DNA hyper-methylation of PITX2 ( paired-like homeodomain transcriptor factor-2) was recently considered as a marker linked to tamoxifen response [52]. A recent study [53] assessed methylation levels of CpG islands promoter of tumour suppressor genes, RARb2, MINT17 and MINT13 during key steps of BC development. They have showed that DNA hyper-methylation of selected biomarkers occurs early in BC development, and may present a predictor of malignant potential [53]. Different epigenetic profiles have also been identified in hormone receptor-positive and -negative tumours [54–56]. The methylation of HIN-1 and RASSF1A strongly correlate with ER and/or PR expression, whereas RIL and CDH13 methylation closely link to negative ER and/or PR. Subsequent studies have shown that the differences of methylation profiles between hormone receptor-positive and -negative breast tumours can also influence tumour response to hormonal therapy like tamoxifen [56,57].


allows reduction of the tumour mass before surgery. NAT can be used to turn a tumour from untreatable to treatable by decreasing the volume. The tumour burden reduction after treatment with NAT influences disease-free survival (DFS), or rather the length of time after treatment during which no disease is found [41]. According to American Society of Clinical Oncology (ASCO) recommendations, tumour biomarkers like oestrogen receptor (ER), progesterone receptor (PR) and HER2 expression should be evaluated in primary invasive BC for diagnosis, disease recurrence and especially as a guide for therapy, while increasing levels of CA27.29 or CA15-3 may indicate treatment failure [42].

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

10. Clinical biomarkers in lung cancer 10.1. The epidermal growth factor receptor

10.2. K-ras (gene expression) K-ras is the most commonly detected mutation in NSCLC. It is more common in tumours with adenocarcinoma histology than in squamous-type NSCLC. K-ras mutation was previously considered a negative predictive biomarker for efficacy of EGFR targeted inhibitors, but, to date, there is no targeted therapy with established efficacy in NSCLC for this genetic mutation. Therefore it does not offer, at present, any clinical value either as a prognostic indicator or as a therapeutic guide. Currently, targeted therapies against activating K-ras mutation are undergoing active testing as a therapeutic strategy in LC [73,74].

11. Epigenetic modifications as biomarkers in lung cancer LC involves an accumulation of genetic and epigenetic events in the respiratory epithelium [75]. Somatic genetic aberrations, such as mutations and copy-number alterations, play a well-known role in oncogenesis, but epigenetic alterations are more frequent than somatic mutations in LC [76]. LC initiation and progression are due to the interaction among

12. Prostate cancer In many countries, prostate cancer (PCa) is the second most frequently diagnosed cancer in males and the second cause of malignancy-related death. The rate of PCa increases significantly after 40 years and about two-thirds of all prostate cancers occur in men 65 years and older [74,87]. PCa may have various clinical courses with different features including slow-growing tumour with no clinical consequences, or rapid development which leads to aggressively metastatic and lethal outcome [88]. The main therapy for patients with metastatic or progressive disease targets androgen production and its mediator, the androgen receptor (AR). These therapies, known as hormonal or androgen ablation treatments, refer to the administration of anti-androgens that block the functional action of AR [89]. Differently from other tumours, PCa biomarkers are usually serum or urine markers, because there are not specific molecular mutations that may be used for prognostic or diagnostic aims. The introduction of PSA has revolutionized PCa screening, and it has ushered in the PSA era; its employment as diagnostic biomarker has allowed an earlier PCa detection, showing an increased incidence. However, its use as a screening tool remains controversial due to unresolved questions about survival benefits, cost effectiveness, and some clinical factors such as the optimal screening age or the PSA levels at which to recommend biopsy [90].

13. Clinical biomarkers in prostate cancer 13.1. Prostate-specific antigen PSA, also known as gamma-semino protein or kallikrein-3, is a kallikrein-like serine protease; a glycoprotein enzyme encoded by an androgen-responsive gene (19q 13.3–13.4). PSA is secreted by the epithelial cells of the prostate gland [91] and it is produced for the ejaculate, where its main role, thanks to the proteolytic function, is to liquefy semen in the seminal coagulum, allowing sperm to swim freely [92,93]. PSA is generally present in small quantities in the serum of men with a healthy prostate, while its levels are often elevated in the presence of PCa or other prostate disorders; for these reasons PSA is the only biomarker that is used for diagnosis and prognosis of prostate tumour [94]. The large use of the PSA test has increased disease detection at earlier stages [95], allowing a decrease in the number of patients in metastatic state [96]. PSA biomarker has been also used as a staging and prognostic tool as its high levels are found in more progressive stages or in


Open Biol. 6: 160254

EGFR is a 170-kDa plasma membrane glycoprotein consisting of a large extracellular region, a single transmembrane domain and an intracellular domain with tyrosine kinase activity and a C-terminal tail. The EGFR family consists of four closely related receptors: HER-1/ErbB1, HER-2/neu/ErbB2, HER-3/ ErbB3 and HER-4/ErbB4 with significant homology in their kinase domains, but differences in the coding regions for the extracellular domain and the C-terminal tails [68]. The molecular analysis of mutations in EGRF gene, its corresponding downstream signalling cascade and the related mutations have led to the development of novel therapies [69]. Data from this biomarker, when combined with analysis of histological material, are becoming very important in LC diagnosis as well as in patient stratification for therapy. EGFR is a widely used therapeutic target to treat patients with NSCLCs. There are mutations that are specific to NSCLCs that activate EGFR. They are deletions in exon 19 and exon 21 point mutation, L585R. These mutations result in ligand-independent activation of EGFR signalling [68]. Two irreversible anti-EGFR tyrosine kinase inhibitors are currently approved for the treatment of advanced NSCLC (gefitinib and erlotinib). Recent phase III randomized trials with these EGFR inhibitors, when compared with chemotherapy, have produced significantly longer DFS, higher response rates, less toxicity and a better quality of life. The ‘combination affinity’ of increased gefitinib and erlotinib with the mutated form of EGFR is expected to represent an approximately threefold improvement over that likely from chemotherapy alone in unselected NSCLC patients [68,70–72].

genetic, epigenetic and environmental factors. The DNA hipo- or hyper-methylation is the most widely form of epigenetic alteration in LC; the presence of hypermethylated gene increases with neoplastic progression from hyperplasia to adenocarcinoma. Many studies have identified a plethora of hypermethylated promoter genes such as RASSF1 [77], CDKN2A [78,79], CYGB [80], RARb [81], APC [77,82], FHIT [83]. RASSF1A is deleted or methylated in 30–40% of NSCLC and 70–100% of SCLC; FHIT is deleted or methylated in 40–70% of NSCLC and 50–80% of SCLC [84]. Methylation of RASSF1A gene combined with K-ras mutation is reported to be a good marker of prognosis in detection of malignancy in false-negative or ambiguous cytology outcomes [85,86].


molecular alterations in the EGFR [66]. However, the lack of a uniform approach to extraction and quantification has made the standardization of any particular biomarker difficult [67].

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

Serum PSA is present in different molecular forms that can be divided into two classes: free PSA (not bound) and complex PSA (bound to protease inhibitors such as a1-antichymotrypsin, a1-antitrypsin, a2 macroglobulin) [97,102]. Free PSA represents 5–45% of total PSA. Its percentage is calculated by free PSA/total PSA  100, and it has been considered as an appendix to total PSA testing, in men with a serum total PSA value of 4–10 ng ml21 [96]. Many studies suggest free PSA as a late-stage predictor of PCa [103] and in particular the percentage of free PSA seems to be inversely associated with risk of finding PCa in biopsy [104]; the researchers show that percentage of free PSA is significantly low in aggressive disease conditions like Gleason score  7, metastases or positive surgical margins [105]. Gleason score is one of the most important predictors of disease outcome. It is a prognostic grading system based only on histological pattern of differentiation and organization of carcinoma cells and its values can change from 2 to 10 [106]. It is found that by using a percentage of free PSA cut-off value of 25%, it is possible to detect PCa with 95% sensitivity and to prevent 20% of unnecessary biopsies [105]. Therefore, percentage of free PSA could be a better predictor of post-operative pathological outcome when compared with Gleason grade [107], even if this opinion has not been confirmed [108,109].

13.3. PCa antigen 3 Urine-based PCa assays have been regarded as a promising tool for the acquisition of highly specific prostatic markers. PCa antigen 3 (PCA3) mRNA expression levels within post-digital-rectal-examination urine have been evaluated as predictors for the PCa detection on subsequent biopsy, whereby higher expression levels of PCA3 have been associated with PCa discovery [110]. A urinary PCA3 assay (Progensa, Hologic Inc., Bedford, MA, USA) is currently approved by the Food and Drug Administration in the setting of prior negative biopsy, where different studies have examined the predictive value of using PCA3 thresholds to select men for repeat biopsy [111].

Epigenetic modifications are heritable and reversible biochemical changes of chromatin structure [112–117]. Unlike mutations that involve an alteration in the DNA sequence, epigenetic modifications regulate gene expression via chromatin remodelling [5]. Among the most well-studied epigenetic modifications are DNA methylation and histone modifications. Epigenetic alterations are frequent in PCa, and they can contribute to the tumour initiation and progression [118]. Although the mechanisms by which these alterations arise are not completely understood, their frequency is commonly higher in premalignant disease stages, giving them an attractive role for diagnosis, prognosis and treatment [6,119–121]. DNA methylation patterns may be the earliest changes in PCa and in effect, many studies have identified a promoter CpG island hyper-methylation of genes, such as GSTP1, APC, RASSF1a, PTGS2 and RARb2; this evidence proposes that multigenes promoter methylation testing could be necessary. A multicentre study has validated the use of three gene panel (GSTP1, APC and RARb2) as a diagnostic maker for PCa [122–125], and moreover several approaches have shown the potential use of PTGS CpG island hyper-methylation as an important tool for recurrence risk prediction [126].

14.1. TMPRSS2-ERG A chromosomal rearrangement in PCa has been identified and associated with earlier precancerous lesions; it is the TMPRSS2-ERG, fusion gene between transmembrane protease serine 2 (TMPRSS2) and v-ets avian erythroblastosis virus E26 oncogene homologue (ERG). Measurement of the TMPRSS2ERG in urine, using quantitative nucleic acid amplification, has been evaluated as a marker, with high specificity for PCa, for disease in the pre-diagnosis setting. The combination of PCA3 levels with TMPRSS2-ERG measurement may offer improved discrimination of disease on biopsy [127,128].

14.2. Glutathione-S-transferase P1 (GSTP1) This gene encodes an enzyme required for DNA detoxification and for its protection from oxidants and electrophilic metabolites, is a potential epigenetic biomarker due to its high specificity (more than 80%) compared with PSA serum. Several studies have focused on the use of GSTP1 as potential diagnostic or/and prognostic biomarker. GSTP1 hyper-methylation levels can be correlated to different disease stages or recurrence risk after treatment and its presence in serum, plasma and urine could be used to screen men when the value of other biomarkers is borderline. However, despite being highly specific, it appears to have a low sensitivity (18–40%) [129–131].

15. Homeostatic biomarkers and role in cancer prediction The human body constantly interacts with the external environment that exposes it to several natural and artificial agents; they can produce irreversible damage or reversible imbalance of homeostatic processes causing various diseases,


Open Biol. 6: 160254

13.2. Percentage free prostate-specific antigen

14. Epigenetic modifications as biomarkers in cancer prostate


more unfavourable result [97]. In spite of this significant role, PSA is organ-specific but not cancer-specific, and therefore it is not a unique indicator of prostate tumour. In fact, serum PSA levels also increase in benign prostatic hyperplasia, in size of prostate secondary to a non-cancerous proliferation of prostate gland cells [93], in the prostatitis (inflammation of prostate), in following interventions like biopsy [98], in older age, in ejaculation and in the use of specific drugs such as male hormones. So only 30% of patients with high PSA have PCa diagnosed after biopsy. Besides, there are several factors that may cause decrease in PSA levels, including 5-a reductase inhibitors, herbal mixtures, obesity, aspirin, statins and thiazide diuretics [99]. One of the main limitations of the PSA test is hence represented by the false positives. Recent data showed that a substantial number of men had PCa with PSA values in the normal range and many of these patients had a high-grade malignant disease [92]. Over the last years, all these observations have impaired the association between PSA and PCa [100,101], and in order to increase PSA diagnostic specificity and prognostic ability, other parameters (such as percentage of free PSA or PCA3) are now increasingly using.

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

16. Discussion and conclusion Translational research on tumour biomarkers has successfully promoted new strategies for therapeutic treatment of cancer, instilling new hopes for cancer patients [150]. Biomarkers can influence the diagnosis and, consequently, the treatment of almost every patient with cancer. Thus, particular emphasis needs to be directed to the clinical approach, which will provide researchers with a critical point of view to improve solutions for patients. The development of new drugs requires high levels of attention and every compound needs to be tested in carefully designed and randomized clinical trials prior to governmental approval. Unfortunately, similar requirements are not mandatory for biomarkers, although they too can significantly influence patient outcomes. Therefore, it is important for clinical, translational and laboratory-based researchers to be acutely aware about the importance of the appropriate biomarker, in order to introduce them in clinical practice. In addition, the introduction of biomarkers that have not been sufficiently evaluated should be avoided because they could not only be ineffective, but even potentially detrimental to patient care. The initial conditions of cancer begin as an imbalance between the instability of the body system and the homeostatic mechanisms. In normal condition, the balance between proliferation and programmed cell death, usually by apoptosis, is strictly maintained by a fine regulation of both processes that ensure the integrity of organs and tissues. Mutations in DNA produce dysregulation and impairment of these regulatory processes, and subsequently lead to cancer. However, genomic and epigenomic alterations do not contemplate the countless interactions of homeostatic processes that occur in every living organism. In our opinion, cancer should not be considered as an indistinct entity in an organism, but as a strongly connected entity with the body


Open Biol. 6: 160254

the whole body. The nervous system is one of the main homeostatic regulation systems, whose alterations could affect its specific control functions; some of these alterations could be represented by stress or depression conditions. Usually, these conditions are more frequent in oncologic patients. Stress or depression conditions influence tumour growth and metastasis development. For these reasons, indirect homeostatic biomarkers, such as epinephrine, norepinephrine and cortisol, can be evaluated. In effect, different studies have demonstrate, in vitro and in vivo, that higher stress hormones can influence proliferation rate, migration, tumour growth and metastasis; these data have also been confirmed by the use of beta blocker agents, suggesting the role of stress markers in the prognosis in various cancer [147–149]. The evaluation of inflammatory/immunity indexes and physiological parameters (cardiac frequency, VO2 max, body temperature and EEG) is important to determinate the complete oncological patient status both in diagnosis and prognosis. For this reason, during follow-up, it is important to check inflammatory profile (PCR, VES, neutrophilia, cytokines, urinary pH), immune outline, oxidative stress markers (endogenous and exogenous antioxidants) and other homeostatic parameters beyond specific molecular disease markers. The prognostic value of these markers is fundamental to evaluate every phase of the pathology progression and treatment response, with the aim to adopt personalized therapies and improve lifestyle, and to improve the patient healing.


including cancer. Homeostasis alterations can influence the function of epigenetic regulation, tissue architecture and immune system play [132 –134]. Homeostasis is a complex process due to the continuous monitoring of several physiological parameters and functions (such as the blood pressure, temperature, acid–base balance and water–salt balance) that are regulated to maintain human body stability; so that the cells can continue to live and work regularly in a suitable environment to their needs [58]. Changes in the homeostatic balance can influence fluid composition; therefore, an environmental alteration (volume and physical–chemical composition) activates the homeostatic mechanism to correct such imbalance and to re-establish all parameters (volume of water, the concentration of ions, hormones, osmotic pressure, oxygen tension and pH) within ‘physiological’ range of values. This mechanism allows a ‘new homeostasis’ inside the tumour due to the cancer cells’ ability to adapt to the environment, establishing new balances, different from previously altered ones. The homeostatic switch can be evaluated monitoring different indexes: metabolic, neuroendocrine, immune and physiological parameters [135]. These parameters can be correlate with tumour progression and they can be considered as prognostic disease markers. The metabolic alterations are the first changes that occur in oncological patients; the typical parameters of this new condition are lactate, enzymatic activities, oxidative stress biomarkers, NOS/ NO, cholesterol and many others [136,137]. Acidosis, for example, is common in cancer, for which homeostatic markers of this condition may be represented by the metabolic enzymes such as LDH or pH parameters like pH extracellular values (Phe), representative of the known Warburg effect (i.e. the phenomenon in which tumour cells rely mainly on glycolysis for energy production even in the presence of sufficient oxygen, which is the most outstanding characteristic of energy metabolism in cancer cells [138,139]). Cancer cells employ this altered metabolism to sustain a high proliferation rate [140]. The lactate dehydrogenase-A that catalyses the inter-conversion of pyruvate and lactate is the main enzyme responsible for the Warburg effect, thus it is upregulated in human cancers and associated with aggressive tumour outcomes [141]. Therefore, in cancer, many studies have targeted the glycolytic pathway, and in particular LDH enzyme, with the aim to develop or to screen new innovative anti-cancer strategies [142,143]. Changes in tumour pHe values can be assessed by different molecular imaging techniques such as 64Cu PET-based imaging, hyperpolarized MRI or acid CEST MRI. Importantly, several studies have shown a correlation between anti-cancer metabolism targeted therapies and reduced growth rate or apoptotic responses, so pHe may be also used, during treatment, as a biomarker for determining drug efficacy and much sooner than detecting a reduced tumour volume with morphological imaging [144]. The TCGA (The Cancer Genome Atlas) project using nextgeneration sequencing has profiled the mutational status and expression levels of all the genes involved in diverse cancers, including those that have a role in cholesterol metabolism, showing the role of the cholesterol pathway in cancer development and supporting a correlation between these genes and the disease prognosis [145]. Neuroendocrine system participate in disease development; the main biomarkers can be catecholamine, ACTC, glucocorticoids, neuropeptide Y, prolactin and serotonin [146]. Homeostatic responses can involve localized body regions or

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018

Competing interests. The authors have no relevant competing interests.

Funding. Financial support from Programma di Ricerca Corrente, Istituto Nazionale Tumori IRCCS– Fondazione Pascale, Progetto ‘I modelli animali per studi traslazionali in oncologia’ (to C.A.).

Acknowledgements. Thanks to Massimiliano Spinelli, Data Manager of SSD Sperimentazione Animale, National Cancer Institute, IRCCS, ‘Fondazione Pascale’, Naples, Italy, for kind help in providing informatics assistance.

References Kalia M. 2015 Biomarkers for personalized oncology: recent advances and future challenges. Metabolism 64(3 Suppl. 1), S16–S21. (doi:10.1016/j.metabol. 2014.10.027) 2. Coppe de` F, Lopomo A, Spisni R, Migliore L. 2014 Genetic and epigenetic biomarkers for diagnosis, prognosis and treatment of colorectal cancer. World J. Gastroenterol. 20, 943–956. (doi:10.3748/wjg. v20.i4.943) 3. Economopoulou P, Dimitriadis G, Psyrri A. 2015 Beyond BRCA: new hereditary breast cancer susceptibility genes. Cancer Treat. Rev. 41, 1– 8. (doi:10.1016/j.ctrv.2014.10.008) 4. Sharma P. 2016 Biology and management of patients with triple-negative breast cancer. Oncologist 21, 1050 –1062. (doi:10.1634/ theoncologist.2016-0067) 5. Schulz WA, Hatina J. 2006 Epigenetics of prostate cancer: beyond DNA methylation. J. Cell. Mol. Med. 10, 100–125. (doi:10.1111/j.1582-4934.2006. tb00293.x) 6. Hake SB, Xiao A, Allis CD. 2004 Linking the epigenetics ‘language’ of covalent histone modifications to cancer. Br. J. Cancer 90, 761–769. (doi:10.1038/sj.bjc.6601575) 7. Burstein HJ, Mangu PB, Somerfield MR, Schrag D, Samson D, Zelman D, Ajani JA. 2011 American society of clinical oncology clinical practice guideline update on the use of chemotherapy sensitivity and resistance assays. J. Clin. Oncol. 29, 3328–3330. (doi:10.1200/JCO.2011.36.0354) 8. Lin K, Lipsitz R, Miller T, Janakiraman S. 2008 Benefits and harms of prostate-specific antigen screening for prostate cancer: an evidence update for the U.S. Preventive Services Task Force. Ann. Intern. Med. 149, 192–199. (doi:10.7326/00034819-149-3-200808050-00009) 9. Zou HZ et al. 2008 Detection of aberrant p16 methylation in the serum of colorectal cancer patients. Clin. Cancer Res. 2002, 188–191. 10. Barrow TM, Michels KB. 2014 Epigenetic epidemiology of cancer. Biochem. Biophys. Res. Commun. 455, 70 –83. (doi:10.1016/j.bbrc. 2014.08.002) 11. Teschendorff AE, Jones A, Fiegl H, Sargent A, Zhuang JJ, Kitchener HC, Widschwendter M. 2012 Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation. Genome Med. 4, 24. (doi:10.1186/gm323) 12. Easton DF, Ford D, Bishop DT. 1995 Breast and ovarian cancer incidence in BRCA1-mutation carriers.














Breast Cancer Linkage Consortium. Am. J. Hum. Genet. 56, 265 –271. Domchek SM et al. 2010 Association of risk-reducing surgery in BRCA1 or BRCA2 mutation carriers with cancer risk and mortality. JAMA 304, 967–975. (doi:10.1001/jama.2010.1237) Grullich C, Von Kalle C. 2012 Recent developments and future perspectives of personalized oncology. Onkologie 35, 4 –7. (doi:10.1159/000334825) Fleming M, Ravula S, Tatishchev SF, Wang HL. 2012 Colorectal carcinoma: pathologic aspects. J. Gastrointest. Oncol. 3, 153–173. Chee CE, Sinicrope FA. 2010 Targeted therapeutic agents for colorectal cancer. Gastroenterol. Clin. North Am. 39, 601–613. (doi:10.1016/j.gtc.2010.08.017) Ahlquist DA, Moertel CG, McGill DB. 1993 Screening for colorectal cancer. N. Engl. J. Med. 329, 1351. (doi:10.1056/NEJM199310283291813) Sinicrope FA, Okamoto K, Kasi PM, Kawakami H. 2016 Molecular biomarkers in the personalized treatment of colorectal cancer. Clin. Gastroenterol. Hepatol. 14, 651– 658. (doi:10.1016/j.cgh.2016.02.008) Grady WM, Pritchard CC. 2014 Molecular alterations and biomarkers in colorectal cancer. Toxicol. Pathol. 42, 124– 139. (doi:10.1177/0192623313505155) Iqbal N, Iqbal N. 2014 Human epidermal growth factor receptor 2 (HER2) in cancers: overexpression and therapeutic implications. Mol. Biol. Int. 2014, 852748. (doi:10.1155/2014/852748) Braun MS et al. 2008 Predictive biomarkers of chemotherapy efficacy in colorectal cancer: results from the UK MRC FOCUS trial. J. Clin. Oncol. 26, 2690 –2698. (doi:10.1200/JCO.2007.15.5580) Downward J. 2003 Targeting RAS signalling pathways in cancer therapy. Nat. Rev. Cancer 3, 11 –22. (doi:10.1038/nrc969) Amado RG et al. 2008 Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J. Clin. Oncol. 26, 1626 –1634. (doi:10.1200/JCO.2007.14.7116) Douillard J, Siena S, Cassidy J. 2009 Randomized phase 3 study of panitumumab with FOLFOX4 compared to FOLFOX4 alone as 1st-line treatment (tx) for metastatic colorectal cancer (mCRC): the PRIME trial. Eur. J. Cancer. 7, S6. (doi:10.1016/ S1359-6349(09)72039-7) Bokemeyer C et al. 2009 Fluorouracil, leucovorin, and oxaliplatin with and without cetuximab in the first-line treatment of metastatic colorectal cancer. J. Clin. Oncol. 27, 663 –671. (doi:10.1200/JCO.2008. 20.8397)

26. Tol J, Nagtegaal ID, Punt CJ. 2009 BRAF mutation in metastatic colorectal cancer. N. Engl. J. Med. 361, 98– 99. (doi:10.1056/NEJMc0904160) 27. Di Nicolantonio F et al. 2008 Wild-type BRAF is required for response to panitumumab or cetuximab in metastatic colorectal cancer. J. Clin. Oncol. 26, 5705– 5712. (doi:10.1200/JCO. 2008.18.0786) 28. French AJ et al. 2008 Prognostic significance of defective mismatch repair and BRAF V600E in patients with colon cancer. Clin. Cancer Res. 14, 3408– 3415. (doi:10.1158/1078-0432.CCR-07-1489) 29. Lao VV, Grady WM. 2011 Epigenetics and colorectal cancer. Nat. Rev. Gastroenterol. Hepatol. 8, 686–700. (doi:10.1038/nrgastro.2011.173) 30. Van Engeland M, Derks S, Smits KM, Meijer GA, Herman JG. 2011 Colorectal cancer epigenetics: complex simplicity. J. Clin. Oncol. 29, 1382– 1391. (doi:10.1200/JCO.2010.28.2319) 31. Sjo¨blom T et al. 2006 The consensus coding sequences of human breast and colorectal cancers. Science 314, 268–274. (doi:10.1126/science. 1133427) 32. Matsubara N. 2012 Epigenetic regulation and colorectal cancer. Dis. Colon Rectum 55, 96– 104. (doi:10.1097/DCR.0b013e318233a1ef ) 33. Nan X, Ng HH, Johnson CA, Laherty CD, Turner BM, Eisenman RN. 1998 Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex. Nature 393, 386–389. (doi:10.1038/30764) 34. Zou HZ et al. 2002 Detection of aberrant p16 methylation in the serum of colorectal cancer patients. Clin. Cancer Res. 8, 188 –191. 35. Antelo M, Balaguer F, Shia J, Shen Y, Hur K, Moreira L. 2012 A high degree of LINE-1 hypomethylation is a unique feature of early-onset colorectal cancer. PLoS ONE 7, e45357. (doi:10.1371/journal.pone. 0045357) 36. Matsunoki A, Kawakami K, Kotake M, Kaneko M, Kitamura H, Ooi A. 2012 LINE-1 methylation shows little intra-patient heterogeneity in primary and synchronous metastatic colorectal cancer. BMC Cancer 12, 574. (doi:10.1186/1471-2407-12-574) 37. Schnekenburger M, Diederich M. 2012 Epigenetics offer new horizons for colorectal cancer prevention. Curr. Colorectal Cancer Rep. 8, 66– 81. (doi:10.1007/ s11888-011-0116-z) 38. Perou CM et al. 2000 Molecular portraits of human breast tumors. Nature 406, 747–752. (doi:10.1038/ 35021093)

Open Biol. 6: 160254




itself. Most importantly, we should improve the diagnostic and therapeutic approach, also considering those markers of homeostasis that are indices of the operation of the body system in toto. We therefore propose a medicine no longer genomic-centric but human-centric.

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018







60. 61.






67. Greenberg AK, Sung Lee M. 2007 Biomarkers for lung cancer: clinical uses. Curr. Opin. Pulm. Med. 13, 249–255. (doi:10.1097/MCP.0b013e32819f8f06) 68. Scott A, Salgia R. 2008 Biomarkers in lung cancer: from early detection to novel therapeutics and decision making. Biomark. Med. 2, 577– 586. (doi:10.2217/17520363.2.6.577) 69. Montuenga LM, Pio R. 2009 Current challenges in lung cancer early detection biomarkers. Eur. J. Cancer. 45(Suppl. 1), 377– 378. (doi:10. 1016/S0959-8049(09)70055-3) 70. Ciardiello F, Tortora G. 2008 EGFR antagonists in cancer treatment. N. Engl. J. Med. 358, 1160–1174. (doi:10.1056/NEJMra0707704) 71. Maemondo M et al. 2010 Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N. Engl. J. Med. 362, 2380–2388. (doi:10.1056/ NEJMoa0909530) 72. Normanno N et al. 2006 Epidermal growth factor receptor (EGFR) signaling in cancer. Gene 366, 2–16. (doi:10.1016/j.gene.2005.10.018) 73. Cappuzzo F et al. 2010 Erlotinib as maintenance treatment in advanced non-small-cell lung cancer: a multicentre, randomised, placebo-controlled phase 3 study. Lancet Oncol. 11, 521– 529. (doi:10.1016/ S1470-2045(10)70112-1) 74. Toyooka S et al. 2011 Molecular oncology of lung cancer. Gen. Thorac. Cardiovasc. Surg. 59, 527 –537. (doi:10.1007/s11748-010-0743-3) 75. Cheng L et al. 2012 Molecular pathology of lung cancer: key to personalized medicine. Mod. Pathol. 25, 347 –369. (doi:10.1038/modpathol.2011.215) 76. Cardarella S et al. 2012 The introduction of systematic genomic testing for patients with non-small-cell lung cancer. J. Thorac. Oncol. 7, 1767– 1774. (doi:10.1097/JTO.0b013e3182745bcb) 77. Graziano SL et al. 1999 Prognostic significance of K-ras codon 12 mutations in patients with resected stage I and II non-small-cell lung cancer. J. Clin. Oncol. 17, 668– 675. 78. Dumitrescu RG. 2012 Epigenetic markers of early tumor development. Methods Mol. Biol. 863, 3–14. (doi:10.1007/978-1-61779-612-8_1) 79. Brzezianska E, Dutkowska A, Antczak A. 2013 The significance of epigenetic alterations in lung carcinogenesis. Mol. Biol. Rep. 40, 309–325. (doi:10.1007/s11033-012-2063-4) 80. Fischer JR, Ohnmacht U, Rieger N, Zemaitis M, Stoffregen C, Manegold C, Lahm H. 2007 Prognostic significance of RASSF1A promoter methylation on survival of non-small cell lung cancer patients treated with gemcitabine. Lung Cancer 56, 115–123. (doi:10.1016/j.lungcan.2006.11.016) 81. Dammann R et al. 2005 CpG island methylation and expression of tumor-associated genes in lung carcinoma. Eur. J. Cancer 41, 1223– 1236. (doi:10. 1016/j.ejca.2005.02.020) 82. Saulnier A et al. 2011 Inactivation of the putative suppressor gene DOK1 by promoter hypermethylation in primary human cancers. Int. J. Cancer 130, 2484 –2494. (doi:10.1002/ijc.26299) 83. Xinarianos G, McRonald FE, Risk JM, Bowers NL, Nikolaidis G, Field JK, Liloglou T. 2006 Frequent


Open Biol. 6: 160254


breast cancer patients. Breast Cancer Res. Treat. 111, 429 –437. (doi:10.1007/s10549-007-9800-8) Van Hoesel AQ, Sato Y, Elashoff DA, Turner RR, Giuliano AE, Shamonki JM, Kuppen PJK, van de Velde CJH, Hoon DSB. 2013 Assessment of DNA methylation status in early stages of breast cancer development. Br. J. Cancer. 108, 2033–2038. (doi:10.1038/bjc.2013.136) Stearns V, Zhou Q, Davison NE. 2007 Epigenetic regulation as a new target for breast cancer therapy. Cancer Invest. 25, 659–665. (doi:10.1080/ 07357900701719234) Giacinti L, Claudio PP, Lopez M, Giordano A. 2006 Epigenetic information and estrogen receptor alpha expression in breast cancer. Oncologist 11, 1 –8. (doi:10.1634/theoncologist.11-1-1) Negrini M, Calin GA. 2008 Breast cancer metastasis: a microRNA story. Breast Cancer Res. 10, 203. (doi:10.1186/bcr1867) Krop IE et al. 2001 HIN-1, a putative cytokine highly expressed in normal but not cancerous mammary epithelial cells. Proc. Natl Acad. Sci. USA 98, 9796 –9801. (doi:10.1073/pnas.171138398) Elaine MN, Katja H. 2007 Human anatomy and physiology, 7th edn. San Francisco, CA: Pearson Benjamin Cummings. Tao AS. Lung carcinoma: tumors of the lungs. Merck Manual Professional Edition, Online edition. See http://www.merckmanuals.com/professional/ pulmonary-disorders/tumors-of-the-lungs/lungcarcinoma. Retrieved 15 August 2007. Falk S, Williams C. 2010 Lung cancer the facts, 3rd edn, pp. 3 –4. Oxford, UK: Oxford University Press. Travis WD et al. 2013 Diagnosis of lung adenocarcinoma in resected specimens: implications of the 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification. Arch. Pathol. Lab. Med. 137, 685–705. (doi:10.5858/arpa.20120264-RA) Sung HJ, Cho JY. 2008 Biomarkers for the lung cancer diagnosis and their advances in proteomics. BMB Rep. 41, 615–625. (doi:10.5483/BMBRep. 2008.41.9.615) Berge EM, Doebele RC. 2014 Targeted therapies in non-small cell lung cancer: emerging oncogene targets following the success of epidermal growth factor receptor. Semin. Oncol. 41, 110–125. (doi:10. 1053/j.seminoncol.2013.12.006) Hirsch O, Witz EA. 2009 Biomarkers for lung cancer screening: interpretation and implications of an early negative advanced validation study. Am. J. Respir. Crit. Care Med. 179, 1–2. (doi:10. 1164/rccm.200809-1395ED) Gomez-roca C et al. 2009 Differential expression of biomarkers in primary non-small cell lung cancer and meta-static sites. J. Thorac. Oncol. 4, 1212 –1220. (doi:10.1097/JTO.0b013e3181b44321) Horn L, Lovly CM, Johnson DH. 2015 Neoplasms of the lung. In Harrison’s principles of internal medicine, 19th edn (eds DL Kasper, SL Hauser, JL Jameson, AS Fauci, DL Longo, J Loscalzo), ch. 107. New York, NY: McGraw-Hill.


39. Palma G et al. 2015 Triple negative breast cancer: looking for the missing link between biology and treatments. Oncotarget 6, 26 560 –26 574. (doi:10. 18632/oncotarget.5306) 40. Zardavas D, Irrthum A, Swanton C, Piccart M. 2015 Clinical management of breast cancer heterogeneity. Nat. Rev. Clin. Oncol. 12, 381 –394. (doi:10.1038/ nrclinonc.2015.73) 41. Llorca P, Radosevic-Robin N. 2016 Biomarkers of residual disease after neoadjuvant therapy for breast cancer. Nat. Rev. Clin. Oncol. 13, 487 –503. (doi:10.1038/nrclinonc.2016.1) 42. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC. 2007 American Society of Clinical Oncology 2007 update of recommendations for the use of tumor marker in breast cancer. J. Clin. Oncol. 24, 5287 –5312. (doi:10.1200/JCO.2007.14.2364) 43. Zaha DC. 2014 Significance of immunohistochemistry in breast cancer. World J. Clin. Oncol. 5, 382–392. (doi:10.5306/wjco. v5.i3.382) 44. Burstein HJ. 2005 The distinctive nature of HER2positive breast cancers. N. Engl. J. Med. 353, 1652–1654. (doi:10.1056/NEJMp058197) 45. Rastelli F, Crispino S. 2008 Factors predictive of response to hormone therapy in breast cancer. Tumori 94, 370–383. 46. Caruso A et al. 2012 Antiproliferative activity of some 1,4-dimethylcarbazoles on cells that express estrogen receptors: part I. J. Enzyme Inhib. Med. Chem. 27, 609– 613. (doi:10.3109/14756366.2011. 603132) 47. Widschwendter M, Apostolidou S, Raum E, Rothenbacher D, Fiegl H, Menon U, Stegmaier C, Jacobs IJ, Brenner H. 2008 Epigenotyping in peripheral blood cell DNA and breast cancer risk: a proof of principle study. PLoS ONE 3, e2656. (doi:10. 1371/journal.pone.0002656) 48. Onitilo AA, Engel JM, Greenlee RT, Mukesh BN. 2009 Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clin. Med. Res. 7, 4 –13. (doi:10.3121/ cmr.2008.825) 49. Montemurro F et al. 2012 Hormone-receptor expression and activity of trastuzumab with chemotherapy in HER2-positive advanced breast cancer patients. Cancer 118, 17– 26. (doi:10.1002/ cncr.26162) 50. Krusche CA, Wulfing P, Kersting C, Vloet A, Becker W, Kiesel L, Beier HM, Alfer J. 2005 Histone deacetylase-1 and -3 protein expression in human breast cancer: a tissue microarray analysis.. Breast Cancer Res. Treat. 90, 15 –23. (doi:10.1007/s10549004-1668-2) 51. Pu RT, Laitala LE, Alli PM, Fackler MJ, Sukumar S, Clark DP. 2003 Methylation profiling of benign and malignant breast lesions and its application to cytopathology. Mod. Pathol. 16, 1095 –1101. (doi:10.1097/01.MP.0000095782.79895.E2) 52. Nimmrich I et al. 2008 DNA hypermethylation of PITX2 is a marker of poor prognosis in untreated lymph node-negative hormone receptor-positive

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018


























prostate cancer with percent free prostate specific antigen: a prospective multicenter clinical trial. J. Urol. 162, 1346–1351. (doi:10.1016/S00225347(05)68282-1) Jung K et al. 2000 Molecular forms of prostatespecific antigen in malignant and benign prostatic tissue: biochemical and diagnostic implications. Clin. Chem. 46, 47 –54. Graefen M et al. 2002 Percent free prostate specific antigen is not an independent predictor of organ confinement or prostate specific antigen recurrence in unscreened patients with localized prostate cancer treated with radical prostatectomy. J. Urol. 167, 1306– 1309. (doi:10.1016/S0022-5347(05) 65287-1) Tomlins SA et al. 2005 Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310, 644–648. (doi:10.1126/ science.1117679) Karpinets TV, Foy BD. 2005 Tumorigenesis: the adaptation of mammalian cells to sustained stress environment by epigenetic alterations and succeeding matched mutations. Carcinogenesis 26, 1323– 1334. (doi:10.1093/carcin/bgi079) Lund AH, van Lohuizen M. 2004 Epigenetics and cancer. Genes Dev. 18, 2315–2335. (doi:10.1101/ gad.1232504) Leader JE, Wang C, Fu M, Pestell RG. 2006 Epigenetic regulation of nuclear steroid receptors. Biochem. Pharmacol. 72, 1589–1596. (doi:10.1016/ j.bcp.2006.05.024) Nightingale KP, O’Neill LP, Turner BM. 2006 Histone modifications: signaling receptors and potential elements of a heritable epigenetic code. Curr. Opin. Genet. Dev. 16, 125– 136. (doi:10.1016/j.gde.2006. 02.015) Lu Q, Qiu X, Hu N, Wen H, Su Y, Richardson BC. 2006 Epigenetics, disease, and therapeutic interventions. Ageing Res. Rev. 5, 449–467. (doi:10. 1016/j.arr.2006.07.001) Garcia-Manero G, Gore SD. 2005 Future directions for the use of hypomethylating agents. Semin. Hematol. 42, S50–S59. (doi:10.1053/j. seminhematol.2005.05.004) Dobosy JR, Roberts JL, Fu VX, Jarrard DF. 2007 The expanding role of epigenetics in the development, diagnosis and treatment of prostate cancer and benign prostatic hyperplasia. J. Urol. 177, 822–831. (doi:10.1016/j.juro.2006.10.063) Jeronimo C et al. 2011 Epigenetics in prostate cancer: biologic and clinical relevance. Eur. Urol. 60, 753–766. (doi:10.1016/j.eururo.2011.06.035) Chan TA et al. 2008 Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis. PLoS Med. 5, e114. (doi:10.1371/journal.pmed.0050114) Baden J et al. 2009 Multicenter evaluation of an investigational prostate cancer methylation assay. J. Urol. 182, 1186–1193. (doi:10.1016/j.juro.2009.05.003) Vanaja DK et al. 2009 Hypermethylation of genes for diagnosis and risk stratification of prostate cancer. Cancer Invest. 27, 549–560. (doi:10.1080/ 07357900802620794)


Open Biol. 6: 160254


97. Shariat SF, Scardino PT, Lilja H. 2008 Screening for prostate cancer: an update. Can. J. Urol. 15, 4363 –4374. 98. Charrier JP, Tournel C, Michel S, Comby S, JolivetReynaud C, Passagot J, Dalbon P, Chautard D, Jolivet M. 2001 Differential diagnosis of prostate cancer and benign prostate hyperplasia using twodimensional electrophoresis. Electrophoresis 22, 1861 –1866. 99. Yuan JJ, Coplen DE, Petros JA, Figenshau RS, Ratliff TL, Smith DS, Catalona WJ. 1992 Effects of rectal examination, prostatic massage, ultrasonography and needle biopsy on serum prostate specific antigen levels. J. Urol. 147, 810– 814. 100. Chang SL, Harshman LC, Presti JCJr. 2010 Impact of common medications on serum total prostatespecific antigen levels: analysis of the National Health and Nutrition Examination Survey. J. Clin. Oncol. 28, 3951–3957. (doi:10.1200/JCO. 2009.27.9406) 101. Stamey TA, Johnstone IM, McNeal JE, Lu AY, Yemoto CM. 2002 Preoperative serum prostate specific antigen levels between 2 and 22 ng/ml. correlate poorly with post-radical prostatectomy cancer morphology: prostate specific antigen cure rates appear constant between 2 and 9 ng/ml. J. Urol. 167, 103 –111. (doi:10.1016/S0022-5347(05) 65392-X) 102. Shariat SF, Abdel-Aziz KF, Roehrborn CG, Lotan Y. 2006 Pre-operative percent free PSA predicts clinical outcomes in patients treated with radical prostatectomy with total PSA levels below 10 ng/ ml. Eur. Urol. 49, 293 –302. (doi:10.1016/j.eururo. 2005.10.027) 103. Thorek DLJ, Evans MJ, Carlsson SV, Ulmert D, Lilja H. 2013 Prostate specific kallikrein-related peptidases and their relation to prostate cancer biology and detection; established relevance and emerging roles. Thromb. Haemost. 110, 484– 492. (doi:10. 1160/TH13-04-0275) 104. Finne P, Auvinen A, Ma¨a¨tta¨nen L, Tammela TL, Ruutu M, Juusela H, Martikainen P, Hakama M, Stenman U-H. 2008 Diagnostic value of free prostate-specific antigen among men with a prostate-specific antigen level of ,3.0 microg per liter. Eur. Urol. 54, 362–370. (doi:10.1016/j.eururo. 2007.10.056) 105. Bickers B, Aukim-Hastie C. 2009 New molecular biomarkers for the prognosis and management of prostate cancer: the post PSA era. Anticancer Res. 29, 3289–3298. 106. Catalona WJ et al. 1998 Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial. JAMA 279, 1542 –1547. (doi:10.1001/jama. 279.19.1542) 107. Buhmeida A, Pyrho¨nen S, Laato M, Collan Y. 2006 Prognostic factors in prostate cancer. Diagn. Pathol. 1, 4. (doi:10.1186/1746-1596-1-4) 108. Southwick PC et al. 1999 Prediction of post-radical prostatectomy pathological outcome for stage T1c



genetic and epigenetic abnormalities contribute to the deregulation of cytoglobin in non-small cell lung cancer. Hum. Mol. Genet. 15, 2038 –2044. (doi:10.1093/hmg/ddl128) Kim DS et al. 2007 Aberrant DNA methylation profiles of non-small cell lung cancers in a Korean population. Lung Cancer 58, 1– 6. (doi:10.1016/j. lungcan.2007.04.008) Virmani AK et al. 2000 Promoter methylation and silencing of the retinoic acid receptor-beta gene in lung carcinomas. J. Natl Cancer Inst. 92, 1303–1307. (doi:10.1093/jnci/92.16.1303) Tomizawa Y et al. 2004 Clinicopathological significance of aberrant methylation of RARbeta2 at 3p24, RASSF1A at 3p21.3, and FHIT at 3p14.2 in patients with non-small cell lung cancer. Lung Cancer 46, 305–312. (doi:10.1016/j.lungcan.2004.05.003) van der Drift M, Prinsen C, Knuiman J, Janssen J, Dekhuijzen PN, Thunnissen E. 2011 Diagnosing peripheral lung cancer: the additional value of RASSF1A methylation and KRAS mutation analyses in washings in non-diagnostic bronchoscopy. Chest 141, 169–175. (doi:10.1378/chest.10-2579) Rauch TA, Zhong X, Wu X, Wang M, Kernstine KH, Wang Z, Riggs AD, Pfeifer GP. 2008 High-resolution mapping of DNA hypermethylation and hypomethylation in lung cancer. Proc. Natl Acad. Sci. USA 105, 252 –257. (doi:10.1073/pnas. 0710735105) Wilt TJ, Ahmed HU. 2013 Prostate cancer screening and the management of clinically localized disease. BMJ 346, 325. (doi:10.1136/bmj.f325) Cary KC, Cooperberg MR. 2013 Biomarkers in prostate cancer surveillance and screening: past, present, and future. Ther. Adv. Urol. 5, 318–329. (doi:10.1177/1756287213495915) Howlader N et al. 2011 SEER cancer statistics review, 1975– 2008. Bethesda, MD: National Cancer Institute. Scher HI, Buchanan G, Gerald W, Butler LM, Tilley WD. 2004 Targeting the androgen receptor: improving outcomes for castration-resistant prostate cancer. Endocr. Relat. Cancer 11, 459 –476. (doi:10. 1677/erc.1.00525) Ross KS, Carter HB, Pearson JD, Guess HA. 2000 Comparative efficiency of prostate-specific antigen screening strategies for prostate cancer detection. JAMA 284, 1399–1405. (doi:10.1001/jama.284. 11.1399) Madu CO, Lu Y. 2010 Novel diagnostic biomarkers for prostate cancer. J. Cancer. 1, 150 –177. (doi:10. 7150/jca.1.150) Rittenhouse HG, Finlay JA, Mikolajczyk SD, Partin AW. 1998 Human Kallikrein 2 (hK2) and prostatespecific antigen (PSA): two closely related, but distinct, kallikreins in the prostate. Crit. Rev. Clin. Lab. Sci. 35, 275 –368. (doi:10.1080/ 10408369891234219) Ilyin SE, Belkowski SM, Plata-Salama´n CR. 2004 Biomarker discovery and validation: technologies and integrative approaches. Trends Biotechnol. 22, 411 –416. (doi:10.1016/j.tibtech. 2004.06.005)

Downloaded from http://rsob.royalsocietypublishing.org/ on April 6, 2018



















medicine in cancer therapy. Evid. Based Complement. Alternat. Med. 2012, 873175. (doi:10. 1155/2012/873175) Glaser R, Kiecolt-Glaser JK. 2005 Stress induced immune dysfunction: implication for health. Nat. Rev. Immunol. 5, 243–251. (doi:10.1038/ nri1571) Di Stefano G, Manerba M, Di Ianni L, Fiume L. 2016 Lactate dehydrogenase inhibition: exploring possible applications beyond cancer treatment. Future Med. Chem. 8, 713–725. (doi:10.4155/fmc.16.10) Hanahan D, Weinberg RA. 2011 Hallmarks of cancer: the next generation. Cell 144, 646 –674. (doi:10.1016/j.cell.2011.02.013) Vander Heiden MG. 2011 Targeting cancer metabolism: a therapeutic window opens. Nat. Rev. Drug Discov. 10, 671 –684. (doi:10.1038/nrd3504) Xie H, Hanai J, Ren JG, Kats L, Burgess K, Bhargava P. 2014 Targeting lactate dehydrogenase-a inhibits tumorigenesis and tumor progression in mouse models of lung cancer and impacts tumor-initiating cells. Cell Metab. 19, 795– 809. (doi:10.1016/j.cmet. 2014.03.003) Kuzu OF, Noory MA, Robertson GP. 2016 The role of cholesterol in cancer. Cancer Res. 76, 2063–2070. (doi:10.1158/0008-5472.CAN-15-2613) Barbieri A et al. 2015 The stress hormone norepinephrine increases migration of prostate cancer cells in vitro and in vivo. Int. J. Oncol. 47, 527–534. (doi:10.3892/ijo.2015.3038) Palma G, De Laurenzi V, De Marco M, Barbieri A, Petrillo A, Turco MC, Arra C. 2012 Plasmacytoids dendritic cells are a therapeutic target in anticancer immunity. Biochim. Biophys. Acta 1826, 407 –414. (doi:10.1016/j.bbcan.2012.04.007) Guo H, Zhou X, Lu Y, Xie L, Chen Q, Keller ET, Liu Q, Zhou Q, Zhang J. 2015 Translational progress on tumor biomarkers. Thorac. Cancer 6, 665–671. (doi:10.1111/1759-7714.12294)


Open Biol. 6: 160254


tumors. Biomed. Res. Int. 2015, 853573. (doi:10. 1155/2015/853573) Tosoian JJ, Ross AE, Sokoll LJ, Partin AW, Pavlovich CP. 2016 Urinary biomarkers for prostate cancer. Urol. Clin. North Am. 43, 17 –38. (doi:10.1016/j.ucl. 2015.08.003) Barbieri A et al. 2012 Role of endothelial nitric oxide synthase (eNOS) in chronic stress-promoted tumour growth. J. Cell. Mol. Med. 16, 920–926. (doi:10.1111/j.1582-4934.2011.01375.x) Palma G et al. 2013 Interleukin 18: friend or foe in cancer. Biochim. Biophys. Acta 1836, 296–303. (doi:10.1016/j.bbcan.2013.09.001) Banfalvi G (ed.). Homeostasis, tumor, metastasis. Dordrecht, The Netherlands: Springer Science. Nogueira V, Hay N. 2013 Molecular pathways: reactive oxygen species homeostasis in cancer cells and implications for cancer therapy. Clin. Cancer Res. 19, 4309–4314. (doi:10.1158/1078-0432.CCR-12-1424) Paesano N, Marzocco S, Vicidomini C, Saturnino C, Autore G, De Martino G, Sbardella G. 2005 Synthesis and biological evaluation of 3-benzyl-1-methyland 1-methyl-3-phenyl-isotioureas as potential inhibitors of iNOS. Bioorg. Med. Chem. Lett. 15, 539 –543. (doi:10.1016/j.bmcl.2004.11.047) Liberti MV, Locasale JW. 2016 The Warburg effect: how does it benefit cancer cells? Trends Biochem. Sci. 41, 211 –218. (doi:10.1016/j.tibs.2015.12.001) Heiden MGV, Cantley LC, Thompson CB. 2009 Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029 –1033. (doi:10.1126/science.1160809) Akhenblit PJ, Pagel MD. 2016 Recent advances in targeting tumor energy metabolism with tumor acidosis as a biomarker of drug efficacy. J. Cancer Sci. Ther. 8, 20 –29. (doi:10.4172/1948-5956. 1000382) Wang Z, Wang N, Chen J, Shen J. 2012 Emerging glycolysis targeting and drug discovery from Chinese


123. Hoque MO et al. 2005 Quantitative methylation specific polymerase chain reaction gene patterns in urine sediment distinguish prostate cancer patients from control subjects. J. Clin. Oncol. 23, 6569–6575. (doi:10.1200/JCO.2005.07.009) 124. Roupret M et al. 2007 Molecular detection of localized prostate cancer using quantitative methylation-specific PCR on urinary cells obtained following prostate massage. Clin. Cancer Res. 13, 1720–1725. (doi:10.1158/10780432.CCR-06-2467) 125. Roupret M et al. 2008 Promoter hypermethylation in circulating blood cells identifies prostate cancer progression. Int. J. Cancer 122, 952 –956. (doi:10. 1002/ijc.23196) 126. Cairns P et al. 2001 Molecular detection of prostate cancer in urine by GSTP1 hypermethylation. Clin. Cancer Res. 7, 2727 –2730. 127. Tomlins SA et al. 2009 ETS gene fusions in prostate cancer: from discovery to daily clinical practice. Eur. Urol. 56, 275–286. (doi:10.1016/j. eururo.2009.04.036) 128. Esteller M. 2005 Aberrant DNA methylation as a cancer-inducing mechanism. Annu. Rev. Pharmacol. Toxicol. 45, 629– 656. (doi:10.1146/annurev. pharmtox.45.120403.095832) 129. Jeronimo C, Usadel H, Henrique R, Silva C, Oliveira J, Lopes C, Sidransky D. 2002 Quantitative GSTP1 hypermethylation in bodily fluids of patients with prostate cancer. Urology 60, 1131 –1135. (doi:10. 1016/S0090-4295(02)01949-0) 130. Gonzalgo ML, Pavlovich CP, Lee SM, Nelson WG. 2003 Prostate cancer detection by GSTP1 methylation analysis of post biopsy urine specimens. Clin. Cancer Res. 9, 2673 –2677. 131. Zmorzyn´ski S, S´widerska-Kołacz G, Koczkodaj D, Filip AA. 2015 Significance of polymorphisms and expression of enzyme-encoding genes related to glutathione in hematopoietic cancers and solid