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Clinical Cancer Research Vol. 11, 3974-3986, June 1, 2005
© 2005 American Association for Cancer Research

Reviews

Prognostic Implications of Cell Cycle, Apoptosis, and Angiogenesis Biomarkers in Non–Small Cell Lung Cancer: A Review

Sunil Singhal1, Anil Vachani2, Danielle Antin-Ozerkis2, Larry R. Kaiser1 and Steven M. Albelda2

Authors' Affiliations: 1 Section of Thoracic Surgery, Department of Surgery, and 2 Pulmonary, Allergy, and Critical Care Division, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania

Requests for reprints: Steven M. Albelda, Pulmonary, Allergy, and Critical Care Division, Department of Medicine, University of Pennsylvania, 8th Floor, BRB II/III, 421 Curie Boulevard, Philadelphia, PA 19104. Phone: 215-573-9933; Fax: 215-573-4469; E-mail: albelda{at}mail.med.upenn.edu.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Angiogenesis
 Conclusions
 References
 
Lung cancer is the leading cause of cancer death in the U.S. with survival restricted to a subset of those patients able to undergo surgical resection. However, even with surgery, recurrence rates range from 30% to 60%, depending on the pathologic stage. With the advent of partially effective, but potentially toxic adjuvant chemotherapy, it has become increasingly important to discover biomarkers that will identify those patients who have the highest likelihood of recurrence and who thus might benefit most from adjuvant chemotherapy. Hundreds of papers have appeared over the past several decades proposing a variety of molecular markers or proteins that may have prognostic significance in non–small cell lung cancer. This review analyzes the largest and most rigorous of these studies with the aim of compiling the most important prognostic markers in early stage non–small cell lung cancer. In this review, we focused on biomarkers primarily involved in one of three major pathways: cell cycle regulation, apoptosis, and angiogenesis. Although no single marker has yet been shown to be perfect in predicting patient outcome, a profile based on the best of these markers may prove useful in directing patient therapy. The markers with the strongest evidence as independent predictors of patient outcome include cyclin E, cyclin B1, p21, p27, p16, survivin, collagen XVIII, and vascular endothelial cell growth factor.

Key Words: prognosis • outcome • survival • genes • lung cancer

Lung cancer is the leading cause of cancer death in the U.S. The American Cancer Society estimates that in 2003, there were >160,000 deaths from lung cancer and >165,000 new cases diagnosed. Of these, non–small cell lung cancer (NSCLC) accounted for ~75%. The most important prognostic variable for survival in NSCLC patients is tumor stage, primarily because early stage disease is amenable to complete surgical resection, hopefully before the tumor cells have acquired the ability to metastasize (1). Only patients who undergo curative surgery have a significant potential for cure (2).

Despite the fact that early stage disease may be cured with surgery, recurrence rates remain high. The 5-year survival rates range from ~70% for stage IA disease to 40% for stage IIB tumors. It is thus likely that many cancers diagnosed as early stage disease have already spread at the microscopic level. In addition, tumors vary in their biological behavior. Some small neoplasms are quite aggressive and, although found at a clinically favorable stage, will progress to widespread, fatal disease.

Given that adjuvant therapies with efficacy in some patients are now available (3–5), the ability to predict survival after lung cancer surgery is even more important because this information could help target therapies to those patients which would obtain the most benefit. An underlying hypothesis of the modern era of cancer research has been that prediction of a patient's prognosis or response to therapy could be improved by combining standard clinical variables (i.e., tumor size, differentiation, or stage), with intrinsic genetic or biochemical characteristics of the tumors. These characteristics have been defined by evaluating the gene expression (by Northern blot and PCR) or protein (using immunoblot or immunohistochemical techniques) levels of selected candidate molecules. Hundreds of studies have evaluated prognostic factors in lung cancer.

We have chosen to focus this review on three important pathways in lung cancer: cell cycle regulation, apoptosis, and angiogenesis. Many of the genes and proteins involved in these pathways have been defined and relevant marker studies focusing on clinical outcome in NSCLC have been done. For a particular marker to potentially have clinical utility, it must provide independent prognostic information. Therefore, in our analysis, particular attention was paid to the analytic methods used to control for the effect of important clinical variables on survival, especially the impact of disease stage. Additionally, results from prospective studies have been highlighted for the few markers for which these studies have been done. We felt that a consolidation of the information available would be helpful in guiding future research. This information may be particularly useful as it will need to be compared with new candidate markers generated by high-throughput measures of gene or protein expression using genomic and proteomic approaches.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Angiogenesis
 Conclusions
 References
 
In order to review the literature for prognostic biomarkers in lung cancer, we did a search on PubMed, a service of the National Library of Medicine, which includes over 14 million citations for biomedical articles dating back to the 1950s (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi). We used the key phrases "lung cancer prognosis protein expression" and "lung cancer prognosis gene expression". This search produced approximately 1,400 papers between 1960 and 2005. In the process of extracting these papers and reviewing them, we screened the references to select other papers that appeared to be appropriate for this review. We used the following criteria to select papers for more detailed reviews: (a) the marker was involved in cell cycle regulation, apoptosis, or angiogenesis, (b) a minimum of 50 patients were studied, (c) the study included stage I and II patients, (d) an attempt was made to quantify the biomarker, and (e) an attempt was made to control for known clinical factors that are associated with outcome.

The main method used to evaluate the effect of a marker on clinical outcome is the analysis of survival curves. This generally includes Cox proportional hazards regression modeling (allowing the comparison of survival in two or more groups while controlling for other variables) or Kaplan-Meier analyses. Proportional hazards regression models allow for the calculation of mortality hazard ratios (a measure of relative risk) associated with a particular risk factor (i.e., biomarker) after controlling for other important variables, particularly disease stage. Kaplan-Meier analysis stratified by disease stage also allows for the assessment of a marker's independent prognostic value. Only studies that used survival curve methods to evaluate the impact of the marker on patient outcome were selected. Studies that controlled for disease stage have been emphasized in the discussion and the associated tables, although studies with important findings are included, even if disease stage was not included in the evaluation.

The tables provide a brief overview of markers evaluated in at least two separate studies and describe the primary method of analysis. If Cox regression modeling was done, hazard ratios and the associated P values are presented. A hazard ratio <1 suggests that increased expression leads to improved survival, whereas a hazard ratio >1 suggests high expression leads to decreased survival. In studies where a stratified Kaplan-Meier analysis was done, the direction of effect (improved survival versus poorer survival) and the associated P value is presented.

The majority of the markers discussed in this review are illustrated in the figures of the three major pathways (cell cycle, apoptosis, and angiogenesis) that were evaluated. Markers were categorized based on the level of evidence as follows: "strong evidence" as a prognostic marker required at least two studies showing a statistically significant effect on survival, with no studies showing the opposite effect on survival; "weak evidence" required one statistically significant study with no studies showing the opposite effect on survival; a "controversial marker" had at least two studies showing opposite effects on survival.


   Results
Top
 Abstract
 Materials and Methods
 Results
Angiogenesis
 Conclusions
 References
 
Cell cycle regulation In nontransformed lung epithelial cells, cellular division is an ordered, tightly regulated process involving multiple checkpoints that assess extracellular growth signals, cell size, and DNA integrity. The replication of DNA occurs in S phase and segregation of the chromosomes into daughter progeny occurs in mitosis (M phase). The two "gap" phases include G1, during which the cell prepares for DNA synthesis, and G2 during which the cell prepares for mitosis (Fig. 1). Cyclins and their associated cyclin-dependent kinases (CDK) are the central machinery that control cell cycle progression. Once activated, the cyclin/CDKs form complexes that initiate phosphorylation of other proteins and downstream cyclin/CDK complexes (see below). Alterations in these proteins, which lead to failure of cell cycle arrest, may thus serve as markers of a more malignant phenotype.



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  		Fig. 1. Cell cycle pathway. The impact of the expression of selected cell cycle genes on NSCLC prognosis was classified as favorable, unfavorable, or controversial. The level of evidence was further evaluated as strong or weak. Uncolored boxes indicate genes that have not been evaluated.evaluated.{04-2661fx01c}, strong evidence for high expression = favorable prognosis; {04-2661fx02c},weak evidence for high expression = favorable prognosis; {04-2661fx03c}, strong evidence for high expression = unfavorable prognosis; {04-2661fx04c},weak evidence for high expression = unfavorable prognosis; {04-2661fx05g}, controversial prognosticmarker; {04-2661fx06l}, not enough data.

 
G1-S transition. Failure of cell cycle arrest at the G1-S transition can cause uncontrolled cellular proliferation (Fig. 1). The product of the retinoblastoma susceptibility gene, Rb, plays a central role in the G1-S transition. In its unphosphorylated state, Rb prevents progression from G1 to S phase by binding the key transcription factor, E2F/DP-1. Once the Rb protein is phosphorylated by the cyclin D/CDK complex, or if Rb is mutated or not expressed, E2F is released allowing transcription of a battery of genes that regulate DNA metabolism. In addition, other CDKs and cyclin molecules are activated. This then enables the cell to pass through a "restriction point" from which the cell proceeds through the remainder of the cycle.

Although abnormalities of Rb expression in NSCLC are common, studies have not consistently showed a difference in clinical outcome related to Rb status (Table 1). In the largest study, which evaluated multiple markers in 408 stage I patients, high Rb expression was associated with an improvement in 5-year survival, although the results did not achieve statistical significance (6). However, the one prospective study of Rb expression found no effect on survival (7).


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  		Table 1. Cell cycle markers

 
Up-regulation of the cyclin D1 proto-oncogene is known to be important in the regulation of the cell cycle pathway. An increase in this gene's expression permits loss of G1 restriction point integrity. Of the four main studies of cyclin D1 in NSCLC, two show improved survival, whereas the other two show poorer survival. In a study limited to stages I and II, cyclin D1 expression was associated with shorter survival and the worst prognosis was observed in tumors with a combination of high cyclin D1 expression with loss of p16 expression (8).

Cyclin E/CDK2 complex can also phosphorylate Rb, as well as other substrates, and is an important regulator of entry into the S phase of the cell cycle. In contrast to cyclin D, cyclin E expression has been consistently associated with shorter survival among stage I to IIIa NSCLC patients undergoing curative resection (Table 1). All studies showed an association between higher cyclin E expression and poorer survival, although the two smallest studies did not achieve statistical significance.

An important mechanism for regulating CDK activity involves the CDK inhibitors, a diverse class of proteins that bind to and inactivate CDKs. These inhibitors are organized into two families based on structure and function: the Cip/Kip family (p21, p27, p57) and the INK4 family (p16, p18, p19). Although the functions of CDK inhibitors are complex, they are generally believed to regulate the cell cycle in response to growth-inhibitory signals, such as DNA damage, hypoxia, serum starvation, and transforming growth factor-ß (TGF-ß). The CDK inhibitor p21 (also known as WAF1, CIP1) inhibits progression through the cell cycle via several mechanisms. It can inhibit the cyclin D/CDK4 and cyclin E/CDK2 complexes early in G1 and it can also inhibit the cyclin A/CDK2 complex later, prior to the S phase/G2 phase transition. In two studies that adequately controlled for disease stage, p21 expression was associated with improved survival (Table 2). Slightly different conclusions were reached by Bennett et al. (9). In an analysis combining p21 and TGF-ß, improved survival was observed in early stage NSCLC when the p21 and TGF-ß were in "concordance" (i.e., either both high or both low expression). A 70% disease-free survival rate was observed in patients with concordant p21 and TGF-ß expression, whereas discordant p21 and TGF-ß expression yielded a disease-free survival rate of 35% (P = 0.0003; ref. 9).


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  		Table 2. Cyclin kinase inhibitors

 
Studies evaluating the effect of p27 expression have also suggested a beneficial effect on lung cancer survival (Table 2). In three studies, p27 expression was an independent prognostic factor for improved outcome (10–12), however Esposito et al. (13) found no effect on survival when results were stratified by disease stage. Similarly, studies of p16 have consistently shown an improved survival with higher expression, although not all studies have reached statistical significance (Table 2).

S and G2. Progression through the S phase is principally regulated by the expression and kinase activity of the cyclin A/CDK2 complex. Both studies that have evaluated cyclin A in NSCLC suggest that increased expression is associated with a poorer outcome (Table 1).

G2-M transition. The second major checkpoint in the cell cycle occurs at the transition from G2 into M. Cyclin B1/CDC2 is the classic M phase–promoting factor that drives entry into mitosis. The association of cyclin B with the active form of CDC2 initiates chromosome condensation, destruction of the nuclear membrane, and assembly of the mitotic spindle. Regulators of CDC2 play a central role in the DNA damage–induced G2 checkpoint, a cellular response to DNA damage that allows time for repair and prevents mitosis of damaged cells. High cyclin B1 expression in stage I NSCLC is associated with a significantly shorter survival time; this effect is seen primarily in squamous cell cancers (14). A more recent study yielded similar results, however, the effect of histology was not evaluated (15).

In summary, cell cycle markers are some of the most powerful predictors of survival. As summarized in Fig. 1, loss of expression of the inhibitors p16, p27, and p21 and/or up-regulation of the cyclins A, E, and B1 all predict a poor prognosis after surgery. The prognostic data for expression of Rb protein and cyclin D are not convincing in NSCLC.

Apoptosis One of the hallmark features of cancer cells is their ability to evade apoptosis. There are two fundamental pathways in apoptosis: the death receptor pathway and the mitochondrial pathway (Fig. 2 shows a very simplified schema of apoptosis). These pathways are intimately connected via caspase 8 and Bid. The first pathway is initiated by cell surface receptor–mediated activation of caspases, a family of cysteine proteases. There are two sets of caspases: initiator caspases and effector caspases. Initiator caspases (such as caspases 8, 9, and 10) transmit apoptotic signals and activate effector caspases (such as caspases 3, 6, and 7) that can then activate degradation enzymes that destroy the cell.



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  		Fig. 2. Apoptosis pathway. The impact of the expression of selected apoptosis genes on NSCLC prognosis was classified as favorable, unfavorable, or controversial. The level of evidence was further evaluated as strong or weak. Uncolored boxes indicate genes that have not been evaluated.evaluated. {04-2661fx01c}, strong evidence for high expression = favorable prognosis; {04-2661fx02c},weak evidence for high expression = favorable prognosis; {04-2661fx03c}, strong evidence forhigh expression = unfavorable prognosis; {04-2661fx04c},weak evidence for high expression = unfavorable prognosis; {04-2661fx05g}, controversial prognosticmarker; {04-2661fx06l}, not enough data.

 
Death receptors. Initiation of the death receptor cascade depends on cleavage of the initiator caspases by the cell surface death-receptors (Fig. 2), which include Fas, tumor necrosis factor receptor-1 (TNFR-1) and TNFR-2. Few studies evaluating the impact of death receptor pathway markers and lung cancer survival have been done (Table 3). In two large studies, expression of Fas was associated with improved survival in NSCLC (16, 17), although the effect was limited to stage III disease in one of the studies (16). Single studies of TNFR-1, TNFR-2, and TNF-{alpha} show that these markers are also associated with improved survival rates in NSCLC patients.


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  		Table 3. Apoptosis

 
Caspases. Studies of caspases in lung cancer outcome are also limited. The two studies of capase-3 expression have shown conflicting effects on survival (18, 19). Caspase-3 can also be regulated by "inhibitor of apoptosis" genes, such as survivin. The survivin gene is a novel apoptosis inhibitor, related to a baculovirus gene. Survivin expression is more frequently increased in lung adenocarcinomas as compared with squamous cell tumors and studies show that high expression was associated with decreased survival in NSCLC (20, 21. Expression of another recently identified gene, antiapoptosis clone 11, was associated with poorer survival (22); however, this result has not been confirmed in other studies.

Death-associated protein. Expression of the death-associated protein kinase is also involved in TNF-{alpha}- and Fas-mediated apoptosis. Lung cancer cells lacking death-associated protein kinase activity seem to be more invasive and have more metastatic potential. In one study of 135 patients with stage I NSCLC, hypermethylation of the death-associated protein kinase promoter was found in 44% of the tumors and was a significant independent factor predicting poorer disease-specific survival (23).

In summary, some mediators of apoptosis may be predictors of survival in lung cancer. As shown in Fig. 2, high expression of apoptosis inhibitors, such as survivin, predicts unfavorable survival, whereas up-regulation of the TNF-receptor, TNF-{alpha}, and Fas, may signal a favorable prognosis.

Bcl-2 family. The mitochondrial pathway is composed of members of the Bcl-2 family of proteins. The Bcl-2 family has both proapoptotic factors (Bax, Bak, Bcl-xs, Bad, and Bid) and antiapoptotic factors (Bcl-2, Bcl-xL, and Bcl-w; Fig. 2). When cells are exposed to apoptotic stimulation, proapoptotic proteins are activated through posttranslational modifications or changes in their conformation. The critical site of action seems to be the mitochondria, where these proteins increase the permeability of the outer membrane resulting in the release of proteins, including cytochrome c, from the intermembrane space. In the cytosol, cytochrome c activates caspase cascades that ultimately lead to cell death.

Studies of Bcl-2 expression and lung cancer outcome have yielded conflicting results. Although one small study showed that high bcl-2 expression adversely affects prognosis (24), several other well-done studies suggest that bcl-2 is an independent prognostic marker of improved survival (25–27), a finding that seems counterintuitive.

Overexpression of Bcl-2 and Bcl-xL are known to inhibit the proapoptotic activity of Bax. In normal cells or tissues, Bax is predominantly located in the cytosol. After apoptotic stimulation, Bax translocates to the mitochondria and forms channels in the mitochondrial membrane. Cells that mutate Bax are relatively resistant to some types of chemotherapy. The impact of Bax expression on lung cancer outcome in early stage disease has not been studied. In one small study of advanced disease, Bax expression was associated with improved median survival in stage IV NSCLC (6 versus 3 months, P < 0.017; ref. 28).

p53. There are abnormalities of the tumor-suppressor gene p53 in more than half of all human malignancies. In addition to its effects on cell-cycle arrest, p53 can induce the apoptosis pathway through induction of Bax. The importance of p53 mutations in the pathogenesis of human lung carcinoma is well established, but it is still controversial whether the presence of p53 mutations or overexpression of p53 protein adversely affects an individual patient's chances of survival. The controversy may be partially due to the methodologic differences in examination for p53 alterations: gene analysis or immunohistochemical staining. Most of the studies focus on p53 expression, whereas others evaluated specific mutations of the p53 gene. These are sometimes related because wild-type p53 has a very short half-life and is not usually visualized by immunostaining of normal cells. In contrast, many p53 mutations markedly prolong its half-life allowing visualization by staining techniques.

The impact of p53 expression on lung cancer prognosis has been studied by multiple groups (Table 4). The four largest studies were limited to stage I patients and have yielded conflicting results (6, 29–31). In the largest study, increased p53 expression had no effect on outcome (31), whereas the other three studies found a slightly increased risk of poorer overall survival (6, 29, 30). The other studies of p53 expression have shown similar conflicting results with hazard ratios varying from 0.5 to 4.5. In contrast to the experience with p53 protein expression, multiple studies of mutational analysis have consistently found mutated p53 to adversely affect survival (Table 4). However, two recent clinical trials of adjuvant therapy following surgical resection analyzed p53 and K-ras abnormalities and found that neither marker added prognostic information (32, 33). Thus, evaluation of p53, either by protein expression or mutational status, is unlikely to be incorporated into clinical practice.


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  		Table 4. p53 tumor suppressor gene

 

   Angiogenesis
Top
 Abstract
 Materials and Methods
 Results
 Angiogenesis
Conclusions
 References
 
Once malignant transformation has occurred, tumor cells, like all cells, require oxygen and nutrients for expansion. When tumors are small (<1 mm in diameter), they rely on diffusion to meet these needs. In order to grow larger, tumors must create a new blood supply to deliver nutrients and oxygen as well as to remove waste products. Angiogenesis is the process by which new capillary beds are formed from preexisting vessels. The angiogenic process is regulated by a balance between stimulatory and inhibitory factors which may be released by the tumor itself or by the surrounding tissues (Fig. 3).



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  		Fig. 3. Angiogenesis pathway. The impact of the expression of selected genes on NSCLC prognosis was classified as favorable, unfavorable, or controversial. The level of evidence was further evaluated as strong or weak. Uncolored boxes indicate genes that have not been evaluated.{04-2661fx01c}, strong evidence for high expression = favorable prognosis; {04-2661fx02c},weak evidence for high expression = favorable prognosis; {04-2661fx03c}, strong evidence forhigh expression = unfavorable prognosis; {04-2661fx04c},weak evidence for high expression = unfavorable prognosis; {04-2661fx05g}, controversial prognosticmarker; {04-2661fx06l}, not enough data.

 
Angiogenic growth factors. Vascular endothelial cell growth factor (VEGF) is a potent growth factor for endothelial cells. Its expression is stimulated by tissue hypoxia, as well as several different growth factors and cytokines. It binds to its receptors, VEGFR-1 and VEGFR-2, causing proliferation and migration of endothelial cells. VEGF also increases vascular permeability and may be involved in the coagulation, fibrinolysis, and apoptosis pathways (34). In contrast to most other markers studied in lung cancer, increased VEGF expression has consistently been shown to adversely affect NSCLC outcome (Table 5)


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  		Table 5. Angiogenesis

 
Platelet-derived growth factor (PDGF) is secreted from platelets and increases DNA synthesis, endothelial cell migration and tumor growth (34). PDGF expression in stromal cells may be more important than tumor cell expression in its effect on angiogenesis and outcome in NSCLC (35, 36). However, the impact of PDGF on clinical outcome remains unclear with two studies showing no effect, whereas a study limited to stage I disease showed poorer survival in PDGF-expressing tumors (Table 5).

Basic fibroblast growth factor (bFGF) is released by proteolytic enzymes from the extracellular matrix, after which it increases the expression of other proteolytic molecules. It is proangiogenic and increases tumor growth (34). Limited studies in lung cancer suggest that bFGF expression is an independent prognostic marker in patients with adenocarcinoma (Table 5); however, the single study in patients with squamous cell tumors did not find a statistically significant effect on survival (35).

Interleukin-8 (IL-8) is angiogenic for NSCLC in vitro and in vivo (37). In one study, high IL-8 expression correlated with a higher microvessel density and was a significant prognostic marker; however, disease stage was not accounted for in the analysis (38). In a follow-up study, this group found an association between the presence of tumor-infiltrating macrophages and tumor IL-8 expression, suggesting a mechanism for how macrophages may adversely affect outcome in NSCLC (39).

Although VEGF, PDGF, bFGF, and IL-8 are the primary growth factors involved in the angiogenic process, several other growth factors also play a role in the development of tumoral blood supply. Hepatocyte growth factor, a cytokine produced by mesenchymal cells, impacts epithelial and endothelial cells through its receptor, the c-met protein. Tissue factor, deposited early in the coagulation cascade, likely plays a role in angiogenesis as well. Limited studies of hepatocyte growth factor, c-met, and tissue factor suggest that these markers may be important prognostic markers in NSCLC (40–43).

Inhibitors of angiogenesis. Tumors may activate angiogenic inhibitors such as angiostatin and endostatin which control growth by suppressing endothelial cell proliferation and angiogenesis and by indirectly increasing apoptosis in tumor cells. Expression of angiostatin has been associated with improved survival (44); however, this study did not control for clinical risk factors. Collagen XVIII, a precursor of endostatin, is associated with a poorer outcome in NSCLC (45, 46), although the reasons for this association are unclear given that higher expression of endostatin would be expected to improve survival.

Markers of angiogenic activity. Angiogenesis is frequently assessed in tumors by evaluating the microvessel count often using antibodies to factor VIII, CD31, or CD34. Although a recent metaanalysis found microvessel density to be associated with poorer survival in NSCLC (47), the impact of microvessel density on clinical outcome remains controversial. This is highlighted by two large studies of stage I disease (6, 31). Each of these studies included >400 patients and evaluated the association of multiple immunohistochemical markers with overall survival. In one study, factor VIII expression was an independent predictor of survival, whereas the other found no effect. There are several likely reasons for this discrepancy. First, these methods assume that the area with the most angiogenic activity reflects the activity of the tumor as a whole. Additionally, these markers do not distinguish between new and old vessels or whether there is actual blood flow through these neovessels (34). High vessel count may solely reflect tumor size and nodal status and therefore may be an unreliable marker in early stage disease.

Multiple Marker Studies. Although most studies to date have studied single markers, interest has also focused on combining the results of two or more markers together to provide prognostic information. In the case of p53, most studies have focused on bcl-2 as the second marker. Two studies suggest that the combination with increased p53 expression and decreased bcl-2 expression portends the poorest survival (27, 48). Similar results have been shown for the combination of p53 and Rb expression (49, 50). The interrelationship between these proteins in the cell cycle and apoptotic pathways may explain this potentially synergistic effect of p53 and bcl-2 or Rb.

More recent studies have tried to evaluate multiple markers simultaneously. Summarizing this literature is difficult given the differences in study populations and the specific markers considered. However, two main conclusions can be made. First, multiple marker studies have not been more successful in identifying promising groups of markers for prognosis in NSCLC. This is highlighted by the experience with p53. Of six studies that have evaluated four or more markers (including p53) simultaneously, three studies found an independent effect of p53 (6, 30, 51), whereas the remaining three did not (24, 31, 52). Second, most of these studies are limited by the large number of hypotheses tested in one group of patients, without confirmation of their findings in any validation cohorts. For example, Volm et al. evaluated 21 markers in 216 NSCLC patients using cluster analysis and found a combination of 9 markers (not including p53) which was associated with long-term survival (53). Although promising, these results may be due to "overfitting" of the data and require confirmation in an external group of patients.


   Conclusions
Top
 Abstract
 Materials and Methods
 Results
 Angiogenesis
 Conclusions
References
 
This review of the literature summarizes a portion of the large number of tumor marker studies that have been reported to predict outcome in patients with resectable NSCLC. It should be acknowledged that this overview is not comprehensive. Although we focused on genes involved in cell cycle regulation, apoptosis, and angiogenesis, there are several other important pathways (e.g., growth factors, DNA repair, cell motility, coagulation) that we did not address. Additionally, we have not discussed evidence to suggest that augmented immune responses to the tumor (i.e., lymphocyte infiltration) can be associated with improved survival.

Several limitations to this review must be acknowledged. There is significant heterogeneity in patient populations (many of these studies include various stages of NSCLC) and in treatments employed. The majority of these studies were retrospective and bias may have been introduced in patient selection. In addition, the length of follow-up in these studies was not constant, and methods of gene expression analysis varied widely and were often not precisely quantitated. Many of the referenced studies failed to categorize their patients' disease as "well", "moderate", or "poorly differentiated" NSCLC. It is therefore possible that the markers were influenced heavily by the differentiation state.

Given these limitations in the currently available literature, however, we did identify several markers that seemed to independently predict patient outcome. Table 6 reflects a summary of some of those genes and proteins that seem to have the strongest evidence (i.e., consistent conclusions in multiple, large, well-done studies) to support their potential use in predicting patient outcome. Whether any of these markers can be used to select patients prospectively for different treatment modalities will need to be evaluated in future studies.


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  		Table 6. Best prognostic markers in NSCLC

 
Up-regulation of cyclin E expression has been clearly shown to be a marker of poor prognosis in resectable NSCLC and is associated with an increased tendency for NSCLC to invade local structures and with poorer survival overall. In contrast, up-regulation of cyclin kinase inhibitors, such as p21, p27, and p16 may prevent tumor cell expansion and lead to improved patient survival.

Expression of apoptotic genes was also associated with prognosis in several studies. Survivin expression was linked to improved survival in NSCLC, whereas studies of FAS, TNFR-1, TNFR-2, TNF-{alpha}, and antiapoptosis clone 11 are also suggestive. The data on caspase 3 and Bcl-2 do not clearly implicate an effect of these two genes on lung cancer outcome.

Angiogenesis also seems to be a critical factor in predicting which patients with resectable NSCLC were likely to recur and eventually die from their disease. High VEGF expression was consistently shown to predict poor outcome. Increasingly convincing studies showing the role of IL-8 in angiogenesis are starting to appear, and one small study suggests an effect of IL-8 expression on clinical outcome. High expression of collagen XVIII, a precursor of the angiogenesis inhibitor endostatin, seems to adversely impact prognosis.

Interestingly, genes known to have prognostic significance in other solid organ tumors, such as Rb, failed to show importance in predicting outcome in NSCLC. Other genes (i.e., cyclin D1, bcl-2) were equivocal in determining patient outcome. This variability may reflect studies that fail to compare equivalent patient populations or studies that may reflect regional influences.

It is relevant to compare the results of this survey to recent studies that have used genomic approaches. Gene expression profiling provides the opportunity to examine thousands of genes simultaneously to discover markers that correlate with patient outcome. Although several studies have begun to evaluate resectable NSCLC and patient outcome (54, 55), there are a number of problems with the genomic data. First, the majority of the genes identified as significant in one study do not match those in other studies. Second, validation in other data sets has proven difficult. For example, when we examined our own gene array data and the data of others, genes identified as important in this review very rarely seem to be associated with prognosis in the genomic studies. Similarly, Beer et al. (54) studied the genetic profile of 86 patients with resectable NSCLC and saw no clear associations with any of the genes mentioned in Table 6, except that VEGF expression was graded according to patient survival. Instead, they identified several novel genes that may be associated with patient outcome such as S100P and crk oncogene. The reasons for these discrepancies are not yet clear. Sample preparation, technical factors, array platforms, and accuracy of clinical information may all be important. Gene expression levels may not always correlate well with protein levels observed using immunohistochemistry. Genomics studies are in their infancy and may reveal new biomarkers to predict patient outcome, however, to date, we are unaware of any validated and reproducible markers.

As noted earlier, most studies to date have focused on only one or a few genes within a certain biological pathway, although studies have begun to look at panels of markers. Given the complexity of the malignant process, we agree that this more comprehensive approach may be helpful. This will likely require the prospective application and quantitative analysis of a carefully selected panel of antibodies used on high-quality NSCLC sections that have been coupled to detailed clinical and pathologic information. Histologic analysis can then be subjected to the appropriate statistical interpretations. The production of tissue microarrays should greatly facilitate this process and allow validation of key antibodies (56–58. As genomic and proteomic technologies improve, it may be possible to define a genetic or protein biomarker expression pattern (in tumor tissues or in serum) using panels of genes or proteins that will allow the physician to map out a specific, individualized therapy for each patient. Given the large amount of data available and the increasing importance of predicting outcome after surgical resection, it is hoped that existing biomarker information will soon be used to help predict patient outcome and direct future patient therapy. This approach has begun to show promise in other types of malignancy, such as breast cancer (59).


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: S. Singhal and A. Vachani contributed equally to this work.

Received 12/23/04; revised 3/10/05; accepted 3/15/05.


   References
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 Abstract
 Materials and Methods
 Results
 Angiogenesis
 Conclusions
 References
 

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