Cancer Biology of Molecular Imaging

  • Steven M. Larson
Living reference work entry


Cancer is a complex series of stepwise genetic alterations resulting in common biologic changes in the transformed cells. Distinguishing features of cancer include rapid proliferation of cells, immortality, resistance to apoptosis, resistance to suppression of proliferation, metastatic behavior, characteristic changes in metabolism, and resistance to immunologic attack. Cancer cells recruit normal host tissues to support growth of the tumor mass.

Fibrocytes and collagen producing cells provide structure for the tumor cells. Endothelial cells are recruited to form blood vessels. Tumor blood vessels have incomplete endothelium, making the vessels leaky. This allows large molecules to leak into the tumor interstitium.

The middle of the tumor mass has few, if any, lymphatic vessels. The combination of vessel leakiness and few lymphatics results in an increased interstitial pressure in the tumor, making it difficult for chemotherapy to diffuse into the tumor mass.

A common anatomic approach to measure tumor response (RECIST) employs measurements of the size of the mass on CT before and 4 weeks after therapy. Total disappearance of the lesion is required for a complete response, a 30% reduction in the sum of long dimensions defines a partial response, and >20% increase in the sum of long diameters identifies progressive disease. Adding metabolic information recorded with [18F]FDG-PET/CT and the PERCIST criteria may refine these measurements. In addition to [18F]FDG, radiopharmaceuticals are available to measure other attributes of the tumor. Depending on the radiopharmaceutical, images can provide information on tumor hypoxia, expression of integrins, or specific tumor markers that are overexpressed by the lesion, such as carbonic anhydrase, expressed by renal cell cancer, or receptors, such as somatostatin, expressed on neuroendocrine tumors.


Cancer biology Molecular imaging 









Anti-CD33 monoclonal antibody labeled with 213-bismuth


ATP-binding cassette




v-Akt murine thymoma viral oncogene homolog 1 (Akt)


Acute myeloid leukemia


Androgen receptor


Adenosine 5´ triphosphate


B-type raf kinase


BRAF-RAS score


Bone scan index


Carbonic anhydrase 9


Cytosine deaminase-5


Complete response


Castrate-resistant prostate cancer


Computed tomography


Cutaneous T-cell lymphoma


Cytotoxic T lymphocyte antigen 4




Deoxyribonucleic acid


Dual oxidase


Epidermal growth factor Receptor


European Organization for Research and Treatment of Cancer


Extravasation and passive retention


Extracellular signal regulated kinase


Anti-1-amino-3-18F-fluorocyclobutane-1-carboxylic acid








Gastrointestinal stromal tumor


Human epidermal growth factor receptor 2


Human glandular kallikrein 2


Herpes simplex virus thymidine kinase gene

HIF-1 alpha

Hypoxia-induced growth factor alpha


Isocitrate dehydrogenase enzymes






MAPK kinase


Part of the name of a specific glioma cell line (U251 MG)


Molecular imaging


Micro ribonucleic acids


Magnetic resonance imaging


Messenger ribonucleic acid


N-acetylated alpha-linked acidic dipeptidase


Nicotinamide-adenine dinucleotide phosphate and its reduced form


National Institutes of Health


Non-small cell lung cancers


Glu-NH-CO-NH-Lys-(Ahx)-[68Ga-HBEDD-CC] conjugate


Poly ADP (adenosine diphosphate)-ribose polymerase


Poly(ADP-ribose) polymerase inhibitor


Paired box gene 8


Programmed death




PET response criteria in solid tumors


Positron emission tomography


Part of the name of a specific BRAFV600K kinase inhibitor (PLX4032)


Prostate-specific antigen


Prostate-specific membrane antigen


Phosphatase and tensin homolog


Nectin 4, a tumor cell marker


Partial response


Retuximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (drug combination)


Response evaluation criteria in solid tumors


Small cell lung cancer


Solute-linked carrier


Six-transmembrane epithelial antigen of the prostate


Standardized uptake value


Standardized uptake value


Thyroid differentiation score


Vascular endothelial growth factor


von Hippel-Lindau

Author’s Introduction

This is the second edition of this chapter with emphasis on the nexus of cancer biology and molecular radio-imaging and targeted therapy. Those who have read the first edition will find much that is familiar, because the foundations for the cancer biology of molecular radiotargeting have not fundamentally changed, even though enrichments have occurred in relevant knowledge. To this end, I have done my best to include updates. The Cancer Genome Atlas is a huge source of knowledge for molecular radiotargeting and has already impacted thyroid cancer radiotherapy. Also, I have expanded the discussion of metabolomics to include glutamine imaging, provided an example of molecular imaging of an oncogene, and elaborated on androgen receptor (AR) and the integrated biochemical system that it drives (the AR axis in advanced prostate cancer). I added a more complete section on tumor immunology, setting the stage for imaging advances that will undoubtedly come in the years ahead. I have discussed the prospective role of radioantibody imaging, as I truly believe that the future will show astonishing advances based on our ability to perform optimization of immune targeting reagents. Elsewhere in this book, much information about specific applications of radiopeptide imaging and therapy, as well as organ-specific applications, is provided. This chapter does not comprehensively cover all molecular imaging but instead discusses key features of relevant cancer biology, as I see it, from the perspective of someone who has focused on oncologic applications of radiotracers for more than 40 years.

When I was a medical student, I was awarded an NIH fellowship to develop a radiotracer probe, technetium sulfur colloid, which is still in use today. This effort set me on the path of nuclear medicine and targeted probe development. As part of my education, my mentor, Wil B. Nelp of the University of Washington, took me to a conference in Richland, Washington, site of the Hanford National Laboratories. Much testing on the radiobiology of radiation was conducted on this campus, which was also the site of development of bomb-grade weapon materials. At this conference, in 1966, I met Shields Warren, a pathologist who was, at that time, a chairman of the Atomic Bomb Casualty Commission, an effort jointly supported by both the Japanese and US Academy of Sciences and the source of much of the current information on human dosimetry and biologic effects. Dr. Warren wrote an inscription on my program that I will never forget: “Congratulations to a student who can start a career with today’s sciences.” To all students of molecular imaging and targeted therapy, now 50 years later, these words are more apt than ever!

Molecular imaging offers quantitative detection of the molecules and molecular-based events that are fundamental to the malignant state, in vivo in living subjects. This is nothing new to nuclear medicine and its clinical applications of the tracer principle, but the opportunities have become so vast in the last decade that new excitement extends well beyond nuclear medicine to energize the whole of oncology. This new excitement stems from the recognition that molecular imaging has the potential to expedite laboratory discovery and personalize the care of individual patients with cancer. In this chapter, we will touch on how facets of the biology of cancer can be exploited in the performance of molecular imaging. This chapter is a revision of that presented in the first edition, with key updates and additions regarding cancer immunology, cancer genomics, pharmacology, and theranostics.

The Evolving Context of Molecular Imaging Practice: The Rapid Pace of Discovery in Cancer Genomics

As we have seen, an important hallmark of cancer is genomic instability and mutation that leads to changes in the genome, some of which have a direct consequence on the development of malignant phenotype (driver mutations), but others (passenger mutations) may be alterations that make the cancer different from normal tissues but have no direct effect on tissue phenotype.

In the last 10 years, revolutionary developments in rapid genomic sequencing have led to a sea change in our understanding of the genetic events important to the process of malignant transformation and maintenance of the malignant state. The practical importance of this new understanding of the cancer genome is that it allows a path forward to implement specific therapies that suppress tumor growth. For patients with lung cancer, for example, modern clinical practice includes a rapid genomic profile that may identify an alteration in the patient’s own tumor, which will likely make it responsive to treatment with specific drugs. As an example, detection of driver mutations based on substitution of leucine for arginine (L858R mutation) in the gene for epidermal growth factor receptor (EGFR) in some lung cancers allows treatment and likely response with erlotinib-targeted therapy. This kind of precision medicine will undoubtedly lead to expanded opportunities for molecular imaging to monitor these targeted treatments and determine, as is often the case, the point in time when the cancer mutates again and escapes from drug control.

As a high-level first pass, most genes that are directly linked to cancer causation fall into two categories: oncogenes, which are driver mutations for a process that leads to cancer, and suppressor genes, which must be disabled to permit expression of the malignant state. Current estimates are that about 140 such genes have been identified in the genome of tumors to date, of which 80 are tumor suppressor genes and 60 are oncogenes [1]. Oncogenes have received more attention from the molecular imaging community because it is easier to image a molecule or molecular-related event that is additive or increased relative to the tissue of origin. Examples include oncogene mutations that lead to HER2 overexpression seen in breast cancer, c-Kit mutations seen in gastrointestinal stromal tumors, and EGFR mutations seen in brain tumors and lung cancers. Examples of suppressor genes include BRCA 1 and 2 mutations, associated with breast, ovarian, and pancreatic cancer; p53 mutations; breast, sarcoma, and brain tumors; and RB gene in retinoblastoma. See specific examples described in the section entitled “Oncogene and Non-oncogene Addiction”.

Hallmarks of Cancer

There is growing acceptance of the view that cancer is “a complex collection of distinct genetic diseases, united by common hallmarks.” Thus, a general and uniting property of cancer is a common phenotype set of “hallmarks,” i.e., the biologic characteristics of malignant tissues that distinguish them from the tissues from which they arise (summarized in Fig. 1).
Fig. 1

Emerging hallmarks and enabling characteristics of cancer (top) and hallmarks of cancer (bottom) (From [2]; permission requested)

Distinguishing features of cancer cells include rapid proliferation, immortality, resistance to apoptosis, resistance to suppression of proliferation, metastatic behavior, and a variety of stress responses, which include a characteristic pattern of metabolism such as the Warburg effect and resistance to immunologic attack that allow cancer cells to better survive in hostile environments. The characteristic behaviors that make a cancer cell malignant are now generally believed to occur through a series of stepwise genetic alterations. In principle, the phenotypic alterations of each of these characteristics are associated with underlying key molecules that can be targeted with selective tracers and images.

The Tumor Mass

A general property essential to the long-term growth of cancer cells is the recruitment of a supporting framework to create the mass that characterizes clinical malignancies. Prior to recruitment of blood vessels, the tumor size is limited by the diffusion distance of oxygen in tissues, which is approximately 100–200 microns. Once a blood supply is established, the tumor mass can grow [2].

Imaging the Tumor Mass

For several decades, observing changes in the size of the tumor mass has been the basis for monitoring treatment response. At first, this was done using palpation, but high-resolution cross-sectional CT imaging rapidly became the gold standard for treatment monitoring once it was developed. At present, clinical imaging criteria have serious limitations for detection of masses, and in most situations, 1 gram of tissue or about 108 cells is a practical limit. The current criteria depend on the measurement of two perpendicular diameters in up to five soft-tissue masses (RECIST 1.1). For a partial response (PR), >30% change is required in the sum of long dimensions of up to two per organ, and for complete response (CR), disappearance of all lesions is required. Progressive disease is >20% in sum of long diameters, validated at 4 weeks after treatment (Fig. 2).
Fig. 2

Fibrocytes, endothelial cells that form vessels which provide nutrients, and immune cells are common constituents of the tumor mass (e.g., which are typically imaged as part of the tumor on CT) (From [2], with permission)

With the widespread introduction of 18F-FDG-PET imaging, there is recognition that metabolic change should also be incorporated into the measurement of tumor treatment response. Initial assessment was based on the EORTC recommendation and employed standardized uptake values for FDG uptake, normalized to body weight (SUVmax) [3]. Expert opinion offers alternative response parameters for making this assessment, such as PERCIST, which incorporates PET SUV measurements into treatment response. PERCIST uses an SUV measure, SUVpeak, which is based on lean body mass, and uses a circular region of 1.2 cm in diameter (with an approximate mass of 1 gram) centered around the hottest voxel, over which the standardized uptake value (SUV) is averaged. In order for PERCIST criteria to be applied to measure tumor response to treatment, the SULpeak must be >/SUL average liver, + 2 standard deviation SUL liver. In this way, tumor and liver SUV are compared [4].

Fox and colleagues have recently proposed an alternative that takes advantage of semiautomated lesion-tracking software to look at all the lesions simultaneously in advanced patients; clearly the size and metabolism of the mass in some combination appear likely to be an important measure of treatment response [4]. It is important to keep in mind that when imaging a tumor mass, changes in a particular parameter involve all of the cells in the mass, both malignant and benign; this is true whether imaging gross anatomic measures obtained by CT or a more tumor cell-associated hallmark such as 18F-FDG uptake due to the Warburg effect.


Once cancer cells are collected into a mass, the cells must recruit blood vessels in order to grow. The blood vessel system in a tumor, called “neovasculature,” has some unique characteristics. The vessels are poorly organized, extremely permeable, and often have an incomplete endothelial barrier. Most tumors have minimal lymphatics in the tumor mass, which causes the mass to have a higher pressure than normal tissue, limiting the diffusion of many molecules (especially antibodies) into the tumor mass. The incomplete endothelial barrier of the neovasculature allows tumor cells direct entry to the host vasculature, providing a path for the tumor cells to circulate and metastasize.

Folkman was the first to recognize that inhibition of angiogenesis could inhibit tumor growth and coined the tumor “angiogenic switch,” for the moment when a small collection of tumor cells begins the vascularization process [5]. Ferrara discovered that vascular endothelial growth factor (VEGF) played a crucial role in the development of neovasculature [6]. In response to VEGF produced at the site of the tumor cells, stem cells are recruited from the bone marrow and migrate to the tumor mass, where they serve an essential role in the production of neovasculature.

Agents that target VEGF and its receptor include the antibody, bevacizumab, and the peptides sorafenib and sunitinib. Bevacizumab binds to VEGF while the peptides interfere with the receptor. Both show strong antitumor activity against some highly vascular tumors, which exert their antitumor effects by inhibiting the VEGF receptor expressed on tumor cells. Bevacizumab has been radiolabeled with zirconium-89 and localizes in breast cancer [7]. In patients treated with these agents, serial imaging with FDG has shown a marked decrease in FDG uptake, reflecting the effectiveness of anti-VEGF therapy on tumor size and metabolism. The response of tumors to therapy such as single high-dose fraction radiation has been linked by some to endothelial damage, whereby radiation induces catastrophic apoptosis in endothelial cells, which results in irreversible damage to tumors.

In contrast to normal vessels, the leaky neovasculature can be exploited to image the tumor mass. The “leaky” incomplete endothelium allows passage and retention of large molecules and nanoparticles into tumors. This process is called the “extravasation and passive retention (EPR) effect ” and is thought to occur because the larger molecules and nanoparticles enter into the perivascular space through relatively large pores, but have difficulty getting back out into the vasculature, much like a lobster has trouble finding its way out of a lobster trap. The continuous expression of angiogenesis factors by the tumor causes a concomitant increased expression of integrin receptors, such as αvβ3 integrin or other members of the integrin family, to provide a homing signal for the cells mobilized to create the new blood vessels for the tumor. Agents binding to this integrin have been synthesized and localized in sites of neovascularity, such as tumors [8] and healing infarcts [9, 10]. Other endothelial sites for imaging include the antigens PSMA, which can be imaged with the antibody J591. In fact, in a review by Schliemann and Neri, nine vascular targets were described for which antibodies have been developed [11].


Solid tumors tend to outgrow their blood supply, causing cancer cells to become hypoxic [12]. The reduced cellular oxygen content that accompanies hypoxia can be imaged using a class of compounds called nitroimidazoles . F-18 misonidazole has been used most often, although numerous alternatives are being developed. The principal localization is passive diffusion into the tumor. Once in the cell, nitroimidazoles undergo a single-electron reduction. In the presence of oxygen, the molecule is immediately reoxidized. As a result, the molecule diffuses back out of normoxic tissue. In the presence of hypoxia, the reoxidation cannot occur, trapping the molecule within the hypoxic but viable tissue. Hypoxia is a key property of tumors that reduces the effectiveness of radiation therapy. Well-oxygenated tissue is about three times more sensitive to radiation damage than hypoxic tissue. Some investigators suggest using F-18 misonidazole to image hypoxic regions within tumors to allow a boost of radiation to the hypoxic region without damaging normal tissues.

Cellular Constituents and Cell-Cell Synergism of the Tumor Mass

The tumor mass contains a mixture of tumor cells and cells recruited from the adjacent normal tissues of the host, such as fibroblasts, collagen fibrils, and vascular endothelium. The amount of stroma is highly tumor dependent, with lesions such as lymphoma having relatively little stroma, and others such as those in the pancreas having relatively few tumor cells and abundant stroma. In addition, tissue macrophages and other immune cells are represented in the mass. Typically, about 3% of cellular mass is represented by endothelial cells. But recent evidence suggests that single-dose fraction radiation’s major effect occurs by selectively damaging the vascular endothelium, the most sensitive cell in the tumor [13].

The mass cannot grow without the active synergism of each cellular component. There is also evidence that cells interact with one another in more subtle ways. Small molecules, large molecular complexes, and entire pieces of membrane are exchanged between tumor cells and supporting stroma. For example, P glycoprotein, an ABC transporter protein responsible for multidrug resistance, was shown to transfer from resistant to sensitive cells, as a functional entity, so that sensitive cells could acquire sufficient resistance to resist otherwise lethal levels of anticancer drugs [14].

Immune Cell Cancer Immunotherapy

Cancer cells may be immunogenic enough to be killed by the natural immunity of the body, as described in Fig. 3. The basis for cancer immunity is thought to be immunogenic products formed as a result of the cancer’s characteristic of rapid mutation leading to “neoantigens,” which are recognized as foreign. Figure 3 depicts the process of immune attack on cancer cells in diagrammatic form, starting with the release of neoantigens by damage to tumor cells, with recognition and process of these antigens by dendritic cells (2), and presentation to T cell in the regional lymph nodes (3). The now immunized T cells migrate through the blood and traverse through the endothelial layer into the tumor mass (5), where they encounter tumor cells (6), recognizing the presence of neoantigens. T cells, most commonly CD8-expressing cells, attack the cancer cell (7). Normally, however, cancer cells escape immune attack based on a system of checks and balances within the tumor cell environment.
Fig. 3

The cancer immunity cycle (From [14, 47]; permission requested)

The cellular component of the tumor mass includes a variety of tumor immune cells, including T cells, macrophages, and dendritic cells, a group of specialized immune cells that are involved as the first line of defense in alerting the immune system to foreign antigens. In particular, activated T cells, especially CD8 expressing cells within the cancer mass, can play a role in cancer therapy. In the last few years, treatment of cancers with immune therapy has led to significant responses—even complete responses—in advanced cancers, especially advanced melanoma and non-small cell lung cancers. The results are so exciting that in 2013, Science magazine selected cancer immunotherapy as the most significant breakthrough of the year [16]. Effective treatments are based on growing knowledge of the role the immune system plays in the delicate balance of immune modulation, a series of checks and balances on the immune response. One of the newly recognized hallmarks of cancer is the ability of cancer cells to suppress the body’s immune response, so much so that the tumor mass is most frequently a sanctuary for proliferation of cancer cells within the tumor mass. Specialized antibody therapies can neutralize key molecules that modulate immune response, and for some tumors, this treatment (“immune checkpoint blockade”) can be part of a potent defense against even the most advanced tumors.

Immune checkpoint blockade. Human T cells are a critical component of the activity of the human immune system as part of body’s primary defense against invasion by foreign tissue and aberrant normal tissues such as cancer. In general, the native proteins in the body do not provoke an immune response in T cells, but among the millions and millions of T cells in the human body, it is thought that there may be a few that can even be immunized against normal macromolecules of normal tissues. But also, a plethora of antigens can be recognized as foreign, including those that may be only slightly different from the native molecules. These differences could arise due to mutation in the gene from which they arise, or from mistakes in the formation of molecules that lead to a slightly altered structure.

One of the ways the immune system is kept in check so that the body does not destroy itself depends on immune suppressor molecules produced by T cells. CTLA4 is an important suppressor molecule expressed by human T cells that are activated against particular antigens. The role of CTLA4 is to downregulate immune response, and CTLA4 increases on the cell surface whenever a T cell is activated, after recognizing an antigen to which it has been immunized. The mechanism whereby this occurs is illustrated in Fig. 4. CTLA4 checkpoint to suppress inappropriate immunity against normal tissues is obviously of great importance for avoiding immunity against self (often called autoimmunity).
Fig. 4

Ipilimumab augments T-cell activation and proliferation (Adapted from O’Day et al. plenary session presentation, abstract #4, ASCO 2010)

It turns out that cancers, and some cancers in particular (i.e., melanoma, non-small cell lung cancer), have a large number of these slightly altered antigens (often called neoantigens) that can create immunized T cells. These genetic changes may be either driver mutations or passenger mutations, but in any event represent altered features of the tissue, which may be recognized by the immune system. This immunity can be enhanced by therapies that block the action of immune suppressor molecule CTLA4 (such as the antibody Ipilimumab), and the result may be long-term anti-cancer response.

In effect, the anti-CTLA4 treatment “takes the brakes off” the human immune system and may have remarkable effects in killing tumor, even in patients with advanced metastatic disease. An additional immune checkpoint system, shown in Fig. 5, involves PD-1, which is expressed on T cells but may be used in the treatment of solid tumor. Some tumor cells, such as lung cancer, downregulate PD-1 by binding to a high-affinity cognate receptor PD L1, which is expressed on some tumors such as NSCLC. The suppressor action of PD-1 is blocked by the antibody nivolumab, and the antibody PD-L1 may have a similar clinical effect. Immune checkpoint alone, and in combination, offers the possibility of curing major human cancers at the stage of clinical development when patients were previously guaranteed to die of their disease.
Fig. 5

Blocking CTLA4 and PD-1

It is important to remember that the immune checkpoint inhibitor antibody is not the agent that actually kills the tumor; it is the body’s own immune cells which do the killing. An additional fact is that the immune cells must be in direct contact with the tumor in order to kill it, and so the immune cells must be able to enter the tumor, if “immune checkpoint” therapy is to be effective.

The tumor mass is an immunologic sanctuary, in that neo-antigens and oncoproteins manufactured by the malignant cell should be more immunogenic than they are in real life. In an exciting new development with profound clinical implications, so-called immune checkpoint blockade antibodies such as ipilimumab (anti-CTLA4) and nivolumab (anti-PD-1) target molecules on tumor-specific T cells that can suppress this antitumor immunity. Both ipilimumab and nivolumab, either alone or in combination, have been introduced into clinical trials and have induced long-term remissions in a significant portion (20–30%) of very advanced and hitherto intractable solid tumors, such as melanoma and lung cancer [17].

The immunologic invasion that follows immune checkpoint treatment, predominantly T cells, can be intense, enough to cause false positives on cross-sectional volumetric PET-FDG imaging. Similar findings were observed after ipilimumab and nivolumab therapy and in this case include increase in size of tumor mass because of immune cell infiltration and false positives on PET. For this reason, modified response criteria have been suggested for monitoring the response profile of solid tumors after these powerful immunologic treatments [18].

Imaging the Immune T Cells

Because of the growing importance of cancer immunotherapy to the treatment of solid tumors, there has been a great deal of interest in imaging the targeting of effector T cells to human tumors. Since the killing of tumor appears to be very dependent on CD8 T cells, this is the group of cells that has been a particular focus. Table 1 summarizes current activity in this area.
Table 1

Examples of radiolabeling of immune T cells in cancer


Disease application (reference)


TIL in melanoma [19]

131I-FAIU /hsvTK

Lymphoma immune cell targeting [20]

111In-anti-CD5 antibody

CTCL in humans [21]

89Zr-anti-CD8 minibody

CD8 imaging [22]

Although immune cell imaging in man is limited, the data available is revealing in light of current knowledge about the importance of tumor to tumor. Figures 6 and 7 illustrate data from a patient with malignant melanoma who was injected with 111In-oxine-labeled lymphocytes, which were elutriated from surgically removed tumors after expansion under IL2 stimulation. Six patients with widely metastatic melanoma were studied. An aliquot of approximately 1010 cells were labeled with 185–399 microcuries of 111In-oxine, rinsed, and, after resuspension in saline, were infused through a filter into the patient. The amount of labeled activity was 3.9 microcurie per 108 cells. Initial distribution as seen in Fig. 8 was observed in the liver, bone marrow, and lung by 2 h, as imaged by planar gamma camera. Sequential studies showed that selective uptake occurred in tumor tissue (see arrows) of up to 40 times the amount in surrounding tissue. Figure 6 shows the time course of uptake, based on regions of interest drawn around six individual tumors in five patients. Localization is seen to increase over time, with a peak at about 72 h. We interpreted this data to indicate that TIL’s were capable of trafficking to tumor after injection. These findings were subsequently confirmed in a larger series of 16 patients. It was of interest that the radiolabeled T cells targeted tumor but did not target lymph nodes.
Fig. 6

(a) Planar images of head and shoulders, thorax and upper abdomen, and anterior and posterior pelvis (moving clockwise from left upper to left lower) 72 h after injection of 111In-oxine-labeled tumor-infiltrating lymphocytes. Localization in the lungs, liver, bone marrow, and melanoma; tumor in lymph nodes of the pelvis and lesions on upper thighs. (b) Time-activity curves over known melanoma tumors, showing migration of radiolabeled TiLs into melanoma tumor sites. (For more details, see [18])

Fig. 7

(a) Anterior pelvis images at 2 and 48 h after intravenous injection of 111In-T101 (anti-CD5 antibody) in patients with cutaneous T-cell lymphoma (CTCL). The antibody binds to the cells circulating in the blood and is internalized, migrating eventually to neoplastic lymphadenopathy in the lymph nodes of the groin. (b) Kinetics of T101-labeled lymphocyte uptake in lymph nodes. The indicated T-cell activity concentrations in blood (cb) and the lymph node tissues are averages of data obtained in four patients. The blood data were used in a nonlinear, least squares fit of the indicated compartmental model to the tissue data. The blood volume parameter Vb was fixed at a representative value of 0.05 ml/g, while the best-fit values (mean ± sem) of the parameters K1 and k2 were determined to be 12.6 ± 0.5 ml/g/h and 0.029 ± 0.002 h-1, respectively

Fig. 8

Progression on bone scan of prostate cancer tumor in bone, measured using the bone scan index (BSI) technique

Fig. 9

The rate of progression of tumor in a group of patients followed a Gompertzian group curve, of the form BSI(t) = BSI0(exp(a/b)(1-exp(−bt))) with an initial doubling time of 45 days, at 3% BSI involvement. Of note is the characteristic decline in rate of growth until a plateau is reached

An indium-111-labeled anti-CD5 antibody, T101, was used to image malignant T-cell lymphocytes as part of a study in mycosis fungoides (cutaneous T-cell lymphoma). Images of the pelvis are shown, at 2 h and 24 h after injection. More than 95% of the radiolabeled T-101 cleared from the blood within 2 h, binding to T65 antigen on T cells, followed by rapid localization, in liver spleen and bone marrow with subsequent gradual clearing of these tissues and concomitant localization to lymph nodes in tumor-involved regions, such as bulky inguinal nodes. Subsequently, using a kinetic model, we estimated the rate of localization of malignant T cells to lymph node in this patient. We calculated that about 3.3 × 107 cells/g/h localized to malignant lymph nodes in this patient and that a plateau occurred at 72 h, when influx was equal to output. At this point, the ratio of cell concentration between lymph node and blood was about 434. Similar studies will likely be performed with improved T-cell labeling methodologies in adoptive tumor cell therapy in man and are likely to give important information about the effectiveness of treatment in individual patients.

The Metastatic Process

Massague and colleagues used a series of passages of human tumors through experimental animals, as a basis for identifying tumor cells with tropism for particular sites of metastases, such as the bone, brain, and adrenals. In breast cancer, individual cells with this tropism were cloned and found to express specific molecules that enabled cells to migrate from the primary site and survive in the new environment [23, 24, 25]. Cells in a metastatic site may reseed the primary tumor, and vice versa, in a continuous exchange [26, 27]. These findings have been observed in animal models of breast, colorectal, and lung cancer and melanoma. This process involves circulating tumor cells in blood, including those which appear “differentiated” for tropism to specific tissues. This “tumor reseeding” may help explain why the growth of solid tumors follows Gompertzian kinetics, namely, an exponentially declining exponential growth in which the tumor doubling times are most rapid at the very earliest stage of tumor growth. Another feature of metastatic growth that supports that concept that tumor cells seed organs via circulation in the blood comes from prostate cancer studies that showed that the sites of early bone metastases correlate with regional distribution within the bony skeleton with active red bone marrow, where blood flow is particularly rich. It was also observed in these patients that progression of tumor volume as a proportion of the bony skeleton followed a Gompertzian kinetic form (Fig. 10).
Fig. 10

The initial metastases in these 27 patients occurred exclusively within the pattern of red marrow distribution in the adult male

Imaging the Cancer Cell

Imaging the cancer cell phenotype: metabolomics . The altered metabolism of malignancy has been exploited for decades to image human tumors (see Table 2 for a list of commonly used metabolic tracers in malignancies). New knowledge is emerging on the metabolomics of human cancers, and there appears to be a growing role for glutamine.
Table 2

Increasing [18F]-FDG uptake and adverse outcome (From [28], with permission)

Tumor type [Ref]

Clinical feature

NSCLC [29]


SCLC [30]


Breast cancer [31]


Thyroid cancer [32]

Survival; 131I uptake

Esophageal cancer [33]

Survival; recurrence

Glioma [34]


Lymphoma [35]


Head and neck cancer

Survival; recurrence

Ovarian cancer




Prostate cancer [36]


The Warburg effect. The Warburg effect (Fig. 11) is the term given to a characteristic metabolic pattern of cancer, in which glycolysis is the dominant means of energy production, even in the presence of oxygen, where most of the carbon atoms from metabolism are secreted in the form of lactate [37]. This excessive glucose utilization by many tumors provides the rationale for FDG PET/CT imaging to identify sites of tumor and evaluate the impact of therapy. More than two million patients per year are imaged with FDG, mostly for the purpose of improved tumor staging, detection of recurrence, and monitoring treatment response.
Fig. 11

Emerging view of the Warburg effect

The initial observation of Warburg was that proliferating tumor cells consume glucose at a higher rate compared to normal cells and that they secrete most of the glucose-derived carbon in the form of lactate rather than oxidizing glucose completely. Warburg’s initial hypothesis included the view that mitochondria must be defective in cancer cells as a basis for the shift to aerobic glycolysis. Recent experiments indicate that in most cancer cells at least, there is no problem with oxidative metabolism in mitochondria, and indeed the conversion of pyruvate to lactate based on lactic dehydrogenase enzyme is an important promoter of growth and tumorigenicity [38].

There is growing awareness that the activation of aerobic glycolysis is just one of the metabolic programs that are crucial to the rapidly proliferating tumor cell. In addition, there is lipid biosynthesis and glutamine-dependent anaplerosis, a term used to describe replacement of intermediates within the Krebs cycle. The purpose of these metabolic flux pathways appears to be threefold: (1) to provide energy for the biochemical processes of growth and metabolism required by proliferating cells; (2) to provide the carbon backbone for key macromolecules such as nucleic acids, lipids, and proteins; and (3) to help control the redox balance within the tumor cell. Signal transduction molecules and gene expression have now been identified that are the natural regulators of these fluxes and include the signal transduction pathways, especially PI3K\AKT\mTor axis, hypoxia-induced growth factor alpha (HIF-1 alpha), and Myc, as some of the more important cellular modulators of metabolism [39].

Thus, a more complete picture is emerging with regard to the altered metabolism of cancer cells. Among the drivers that stimulate the altered metabolism, the tumor microenvironment tends to be hypoxic with increased concentrations of HIF-1 alpha and oncogenic signaling, through a variety of known oncogenes such as Ras or Myc. In addition, suppressor proteins like p53 may play a role. The p53 suppressor protein stimulates the gene encoding synthesis of cytochrome c oxidase protein, so when p53 is disabled by mutation, there is direct interference with the mitochondrial respiratory chain. The altered metabolism confers certain advantages, such as increased biosynthesis of nucleotides, proteins, phospholipids, and fatty acids; increased glycolysis also directly inhibits apoptosis by neutralizing reactive oxygen species through the production of NADPH. In addition, there are liabilities with this approach, because toxic metabolites such as lactate and noncanonical nucleotide species tend to accumulate. Finally, a high energetic demand requires that alternative substrate such as fatty acids may need to be converted to ATP in order to meet the energy requirements of the cell [40].

Recently, glutamine has been recognized as an essential nutrient for cell growth and viability of some cancers, and in fact, tumor cells can become “addicted” to glutamine. In this case, the tumor cells fuel their growth by a combination of glucose and glutamine. Whereas PI3K and AKT are the important signal transduction molecules which control glucose uptake, recent studies suggest that MYC oncogene may be crucial for the control of glutamine uptake. Glutamine plays a key role in maintenance of Krebs cycle intermediates, as well as providing energy in the form of ATP [41]. Thus in the situation of active glutaminolysis, glucose and glutamine are the source of energy, and most of the other substrates which are taken up contribute to macromolecular synthesis.

Figure 12 shows glutamine uptake in brain tumor compared to FDG imaging. In some cases, 18F-glutamine may be superior to FDG imaging, because there is negligible uptake of glutamine into cerebral cortex, unlike FDG, uptake driven by glycolysis, and the brain is an obligate user of glucose. From this, it is clear that certain oncogenes, with known functions such as the receptor tyrosine kinases, interact with metabolism through PI3K/AkT/mTor pathway. PTEN, as a natural inhibitor of this pathway, would be expected to have a role in metabolic activation. Other tumor suppressor proteins such as p53 are also thought to have an emerging role in modulating cancer cell metabolism, particularly by favoring oxidative phosphorylation and reducing glycolysis when active. When p53 is deactivated by mutation, glycolysis is favored.
Fig. 12

Uptake in brain tumor: glutamine vs. FDG (Courtesy of Mark Dunphy, DO of MSKCC)

Additional metabolic enzymes that may have oncogenic function include fumarate hydratase (associated with leiomyosarcoma) and succinate dehydrogenase (paraganglioma). When these enzymes are defective, accumulation of fumarate and succinate occurs. The excess of these metabolites causes overexpression of Hif-1 alpha, which promotes the vascularization of tumor as well as increased glycolysis, and may explain the tumor development. Recently, 70% of gliomas have been found to have mutations in isocitrate dehydrogenase enzymes (IDH1 and IDH2), suggesting a role for metabolic enzymes as oncogenes or tumor suppressors [42]. Data recently reported suggests that this mutation in IDH1 is not a loss of function but instead leads to the ability to produce 2-hydroxygutarate, a metabolite whose excess has been associated with human malignancy in patients with inborn errors of 2-HG metabolism [43].

Correlation of increased FDG uptake with poor prognosis. Molecular imaging of radiotracers has been greatly enhanced by the introduction of relatively simple quantitative concepts, such as standardized uptake value (SUV). The SUV is a relative uptake in tissue (commonly tumor), corrected for body size and amount of injected activity, and may be expressed as maximum SUV in a region, average SUV, corrected for body weight, lean body mass [44]. (As a mass correction, lean body mass is preferred, since there is the least correlation of this parameter with tumor uptake and blood SUV. Tumor response based on SUV measures has recently been proposed in the “PERCIST” algorithm, and the advantages of PET-FDG imaging based on SUV measures for monitoring treatment response has been proposed [4]. The SUV in various forms is available as a standard measure on most PET cameras in use over the past 10 years. Therefore it is no surprise that correlations with prognosis and SUV have been estimated for a variety of tumors. Table 2 is a list of tumor types which have shown a strong inverse correlation of SUV with prognosis.

Proliferation Imaging

Tumor tissue has an accelerated rate of growth, and this process can be measured by evaluating changes in volume by CT imaging or by molecular imaging of processes that are accelerated during cell division, in particular, the synthesis of DNA and its intermediates. A diagram of the key biochemical form is provided showing the structure of several of these. Several tracers have been proposed to study this phenomenon. DNA may be built up from component bases, as shown in Fig. 13. The bases are added to the pentose sugar ribose to form the nucleoside cytosine, uridine, and thymidine, with subsequent phosphorylation, to the triphosphate, using thymidine kinase. The exchange is quite rapid between tissue and blood during periods of tumor growth, and nucleosides like thymidine are rapidly added to the DNA chain, at the appropriate site (see below). The DNA strand is built up base by base along a backbone formed by the linked sugar molecules, proceeding from the replication fork, thymidine binds to adenine (T-A), cytosine binds to guanine (C-G), and a triplet of bases encode for a single amino acid.
Fig. 13

DNA synthesis. The four component bases found in DNA are adenine (abbreviated A), cytosine (C), guanidine (G), and thymidine (T)

18F-FLT Imaging of Proliferation After Chemotherapy

Several tracers have been proposed to study this phenomenon, and chemical structures of a group of pyrimidine-based tracers are shown in Fig. 14. Of these, FLT, or fluoro-L-thymidine, is the most important and has been used extensively in clinical trials. An example is shown of the effect of chemotherapy on the uptake of F-18 FLT in lymphoma is shown in Fig. 15.
Fig. 14

Chemical structure of key purine and pyrimidine intermediates, along with pattern of phosphorylation prior to incorporation into DNA

Fig. 15

18F-FLT imaging after chemotherapy in non-Hodgkin’s lymphoma. The patient is imaged after two cycles of RCHOP chemotherapy. The upper row is the baseline study and the bottom row is post-therapy. There is rapid proliferation at baseline, which is stopped by effective therapy

The patient in Fig. 15 was imaged after two cycles of RCHOP chemotherapy. The upper row is the baseline study and therapy. Abnormal proliferation is an important component of the malignant state, and a tracer such as FLT has potential for major benefit in evaluating tumors. FLT is taken up by nucleoside transporters on the membrane of tumor cells, is phosphorylated by thymidine kinase, and used in the exogenous pathway under the enzymatic control of thymidine kinase, but is not incorporated into DNA. The phosphorylated form is retained in tumor.


Apoptosis is an important process in the life cycle of normal cells. Programmed cell death allows the cell to undergo an energy-dependent well-orchestrated process of involution. Apoptosis can be induced by both intrinsic and extrinsic pathways, and one of the hallmarks of cancer is resistance to the apoptotic process [45]. Overcoming this resistance through therapy may contribute to accelerated treatment response in some patients. One of the earliest events in the process of apoptosis is a reversal of the normal cell membrane lipid structure, with exposure of phosphatidylserine on the outer leaflet of the cell membrane. In normal cells, phosphatidylserine is confined to the inner leaflet of the cell membrane. The externalization of this phospholipid allows the involuting cell to bind selectively to clotting factors and proteins. A physiologic protein, annexin V, has an affinity of >10−8 for membrane-bound phosphatidylserine. This protein has been labeled with technetium-99 m and was found to localize at sites of apoptosis both in experimental animals and in patients undergoing chemo- or radiotherapy. Apoptosis also occurs in non-neoplastic conditions, such as immune-induced inflammation and acute myocardial infarction. An alternative to annexin as a marker of apoptosis has been developed by comparing many different factors that bind to apoptotic cells.

PARP is an important enzyme in the repair of DNA and is highly overexpressed in cancer. Recently PARP-1 has been recognized as an important therapeutic target in many tumor types. Imaging agents have been developed that successfully image animal models of orthotopic glioblastoma tumors, with uptake that can be blocked by therapeutic PARP-1 inhibitor drugs (Fig. 16).
Fig. 16

In vivo whole-body PET/CT imaging of [18F]PARPi in orthotopic brain tumor-bearing mice. (a) Fused PET/CT coronal images of a brain orthotopic U251 MG tumor-bearing mouse acquired at 2 h postinjection of [18F]PARPi (left) or the blocking agent olaparib (500-fold excess) followed by [18F]PARPi (right). (b) PET quantification of U251 MG tumors from images acquired at 30 min and 2 h postinjection (n = 10) (Courtesy of Drs. Thomas Reiner and Wolfgang Weber, MSKCC; from [46])

Oncogene and Non-oncogene Addiction

Cells that are nonmalignant reside within a particular tissue and receive growth and other control signals through a network of signal transduction molecules, which are illustrated diagrammatically as a series of interconnecting lines (Fig. 17). In cancer cells, the process of intracellular communication may be co-opted by specific driver mutations in otherwise normal genes, leading to an abnormal gene called the oncogene. The oncogene produces abnormal gene products, oncoproteins, that drive oncogenesis and lead to malignant cell behavior. Driver mutations that are examples of oncogene addiction include overexpression of HER2 in breast cancer, c-Kit mutation in GIST, and ABL kinase mutation in leukemias. Mutations can occur in kinases, which have a signal transmitting function; this can disrupt functioning. Examples include EGFR mutations, c-KiT mutations, and ABL kinase mutations. Other commonly mutated oncogenes include genes controlling Rb, P53, and PTEN, proteins that suppress a tendency toward tumor formation. In fact, cancer occurs when a series of mutations have developed that cooperate to create the complex malignant phenotype.
Fig. 17

Diagrammatic illustration of a network of signal transduction molecules as a series of interconnected lines. They transmit growth and other control signals to nonmalignant cells that reside within a particular tissue (From [2, 47], with permission)

Examples of Imaging the Action Driver Mutations in Cancer Cells Indirectly Through Effects on Metabolism

The mutations that drive the cancer cell into the malignant state can be thought of in three categories: gain-of-function mutations, translocations, and amplifications. Treatments and imaging are focused on these driver mutations, and in particular, the success of kinase inhibitors has validated this concept.

BRAF Inhibition in Advanced Melanoma with V600E Mutation

The highly specific tyrosine kinase inhibitor PLX 4032 appears effective in patients with metastatic malignant melanoma. About 70% of melanomas have a significant response based on RECIST 1.1 criteria when treated with PLX 4032. Eighteen patients had a CR and one patient had a PR. Patients had a rapid response to the drug, with marked reduction of FDG uptake. For therapy to be effective, PLX 4032 must be administered at a dose sufficient to inhibit >80% of the BRAF pathway [48] (Fig. 18).
Fig. 18

Of 27 patients, three are shown: baseline study (left) and follow-up at 2 weeks posttreatment (right) (From [47], with permission)

Inhibition of MEK, a Downstream Signal Transduction Molecule in the RAS/BRAF/ERK Pathway, Can Reverse 131I Resistance in Patients with Thyroid Cancer

Thyroid uptake of iodine in papillary thyroid cancer occurs because of a set of thyroid genes responsible for iodine transport and organification in normal thyroid tissue. These genes are often lost during cancer formation. Recent data mining in the databases for papillary thyroid cancer has led to important correlations between driver mutations responsible for tumor formation, such as the V600E mutation in BRAF, as well as driver mutations in RAS. Agrawal and colleagues have developed a thyroid differentiation score (TDS) consisting of nine genes integral to iodine uptake and differentiation. A heat map of these genes is shown in Fig. 19. In general, the vertical columns, which are mostly red, have higher differentiation scores.
Fig. 19

Thyroid differentiation score (TDS) across the cohort with tumors sorted by driver mutation and TDS. Below TDS are the BRAF V600E-RAS score (BRS), ERK signature, histological type, MACIS score, risk of recurrence, driver mutations, and gene expression data for nine thyroid genes used to derive the TDS [TG, TPO, SLC26A4 (pendrin), SLC5A5 (Na/I symporter), SLC5A8 (apical iodide transporter), DIO1, DIO2, DUOX1, and DUOX2)], four selected mRNAs correlated to TDS, and three selected miRs correlated to TDS. Featured mRNA (except for 16 thyroid genes) and miRNA genes were selected based on Spearman correlation to TDS in the BRAF V600E cohort (*) and the full cohort (**) (From [49], with permission)

Abnormalities of the BRAF/ERK signaling pathway promote the malignant state in thyroid cancer, and inhibition of MEK leads to redifferentiation of experimental models of human thyroid cancer in animals (James Fagin, personal communication, Sloan Kettering Institute). Patients with I-131 refractory thyroid cancer were treated with the MEK inhibitor AZD 6244 for 5 weeks and then restudied with quantitative PET imaging using iodine-124. Approximately two-thirds of the patients had restoration of radioiodine uptake and went on to be treated with 131I-iodide, with excellent clinical response to treatment (Fig. 20) [50].
Fig. 20

In baseline scan, upper image, coronal projection, arrows point out metastatic sites of pulmonary metastases that do not take up radioiodine at 48 h after oral administration. In the lower image, taken 5 weeks later after treatment with the MEK inhibitor AZD 6244, all of these lesions have taken up sufficient amounts of radioiodine to predict therapeutic effect. This patient had a reduction in size of pulmonary nodules as well as significant fall in serum thyroglobulin (Data not shown)

Imaging the Driver Oncogene in Castrate-Resistant Prostate Cancer: The Androgen Receptor Axis

Dihydrotestosterone, a metabolite of testosterone, is the most abundant androgen at the tissue level in vivo and binds to AR in vivo. We have extensively studied a radiolabeled analog, 18F-FDHT, to explore AR expression and in vivo binding in patients with the lethal form of prostate cancer, namely, castrate-resistant prostate cancer (CRPC). Toxicity, patient dosimetry, conditions of use, and optimized analysis were assayed, and FDHT continues to be used in a variety of clinical trials that are ongoing, e.g., 00–095 in metastatic CRPC [51, 52, 53, 54].

We have adapted this approach to the study of AR expressing primary and metastatic prostate cancers. We directly image AR under a short-time medical castration to testosterone levels < 50 pg/ml. We have also used glycolysis marker FDG, a clinical standard tracer, within 24–48 h as a marker of active tumor metabolism, and have demonstrated high patient acceptance of a two-day sequence of imaging, requiring about 1 h of scanning each day. In addition, we have analyzed imaging biopsies to explore the presence of the downstream androgen effector proteins, particularly HK2, PSMA, and STEAP [55, 56, 57] for consideration of later AR-axis monitoring using radiolabeled antibody approaches as a possible pharmacodynamic approach of AR-axis inhibition in later drug trials.

The rationale for this approach is summarized in Fig. 21, which is a diagrammatic representation of the binding of the radiolabeled agonist, FDHT to AR, with the subsequent translocation to the nucleus with binding to hormone-responsive elements on DNA that cause downstream androgen effects.
Fig. 21

(a) Model of AR axis. (b) FDHT before (top) and after (bottom) treatment with enzalutamide to suppress AR uptake of FDHT along the spine. (c) 89Zr anti-STEAP imaging shows uptake in metastases along the spine. The AR axis is driven by androgens that bind to AR in cytoplasm and transport to the nucleus, where the AR complex binds to hormone-responsive elements. Downstream effectors that are activated may be imaged, such as PSMA, PSA, HK2, and STEAP (See [58] for details)

Androgen Receptor (AR) as Oncogenic Driver in Prostate Cancer

AR is activated in CRPC, the lethal form of the disease. AR inhibitors are an important component of therapy in this disease. Figure 21 shows the application of MI in the form of 18F-FDHT (16β-fluoro-dihydrotestosterone), an AR-binding ligand. Recently, effective androgen blockade agents have been introduced for therapy of prostate cancer. Figure 22 shows baseline uptake of FDHT in the metastatic tumor in the vertebrae of a patient with CRPC. All 22 patients treated in this Phase I trial showed displacement of FDHT tracer by the AR-binding drug MDV3100, indicating that the AR displacement agent was hitting the AR target. The AR axis is responsible for downstream effector molecules that are a part of the androgen effects. For example, common proteins produced by prostatic-like tissues include the four listed in Fig. 21: STEAP, a membrane transport protein; PSMA, a NAALADase enzyme; and PSA and HK2, kallikrein-related peptidases produced to keep semen liquified, thus enhancing sperm motility.
Fig. 22

Left, top: Baseline sagittal PET imaging obtained with the radiotracer 18F-FDHT (16β-fluoro-dihydrotestosterone). Left, bottom: Image obtained 4 weeks after injection of beginning treatment with MDV3100, an AR blocker. The radiotracer is the analog of the dominant androgen at the tissue level in man, namely, dihydrotestosterone (DHT). Right: background-corrected changes in average SUVmax for all lesions in the treated patients. Therapy of prostate cancer. Fig. 8 shows baseline uptake of FDHT in the metastatic tumor in the vertebrae of a patient with CRPC. All 22 patients treated in this Phase I trial showed displacement of FDHT tracer by the AR-binding drug MDV3100, indicating that the AR displacement agent was hitting the AR target

Imaging of Carbonic Anhydrase 9 as a Pathognomonic Indication of Clear Cell Renal Cancer

A driver mutation occurs in renal cancer with mutation of the von Hippel-Lindau (VHL) protein. At normal levels of tissue oxygen, VHL is tightly bound to the transcription factor Hif-1alpha, inactivating it. In renal cell cancer, there is an inactivating mutation of VHL, and Hif-1 alpha is continuously activated, with chronic production of downstream effector proteins, especially VEGFR, and also carbonic anhydrase 9 (CA9) , as proteins that are normally activated in hypoxic tissues. Clear cell renal cancer is produced in this setting. 124I-cG250 is a positron-emitting antibody that targets CA9, which has been introduced to assist in surgical planning of masses of the kidney. As shown in Fig. 23, there is uptake in a mass in the kidney bed with excellent contrast, at 7 days after injection of 124I-cG250 [59]. Targeted therapy with sunitinib and sorafenib is used in this clinical setting to block the action of VEGFR.
Fig. 23

Uptake in a mass in the kidney bed with excellent contrast, at 7 days after injection of 124I-cG250

Future Applications

Many other molecular imaging approaches are available to characterize one or more aspects of a neoplasm, including F-18 estradiol for breast cancers, amino acid incorporation (FACBC, glutamate), 68Ga-PSMA for prostate imaging, and 68Ga-DOTATATE for neuroendocrine imaging. Some of these have been approved, and others will likely be available within the next 5 years. However, due to the lengthy process of regulatory approval, the major radiopharmaceutical for evaluation of the tumor patient will remain FDG. With increased understanding of changes in glucose transporter expression by the tumor cell, it is likely that more sophisticated prognostic indices than SUVmax may be developed. It is also likely that genomic analysis of circulating tumor cells may be used as a gatekeeper, to determine if a more selective MI probe PET/CT study is likely to provide clinically useful information.

The development of radiotracer probes for molecular imaging continues to proceed at a very rapid pace. Moreover, drug companies are beginning to recognize the important role that molecular imaging can play in facilitating drug development through an improved understanding of the biology of the cancer process. It is highly likely that very soon we will see ever more remarkable radiotracers, probably in combination with MRI agents and optical agents, because of the ease with which fusion imaging may be obtained in order to exploit the combined information. The field of nanotechnology offers many opportunities for probe development, including serving as a carrier for highly selective radiotracers such as complementary probes like DNA-binding or RNA-binding proteins, as well as radiolabeled drugs. Theranostic agents combine the potential for diagnosis and therapy, so that agents are not only intended to visualize tumors but in effect guide therapeutic delivery. This is already beginning in the exciting field of image-guided interventional radiology, but will extend to tracers with both diagnostic and therapeutic potential. For example, it is easy to contemplate the radiolabeled drug carried in nanoparticles so that the quantification of the payload delivered will serve as a sensor that provides, through quantitative imaging, the total amount of drug that is both taken up and retained within the tissues. Such theranostic approaches will improve selection of patients for a given type of therapy and may allow for tailoring treatment to the individual patient.

Radioantibody and Radiopeptide Imaging and Therapy (Theranostics) Will Drive Our Field for the Next Decade and Beyond

Radiolabeled antibodies and peptides have been used for molecular imaging and in some cases therapy due to the highly selective nature of the antibody-antigen bond. Advances in the molecular biology of antibody production have greatly improved antibodies both as therapeutics and as carriers of radioactive, toxin, or chemotherapy payloads. A table of commonly used antibodies for targeting and therapy applications at MSKCC is shown below (Table 3). Antibodies fall in one of the most rapidly expanding categories of new drugs, and successful drugs include Herceptin (HER2), Avastin (VEGF), rituximab (CD20), ipilimumab (CTLA4), cetuximab (Erbitux), and panitumumab (Vectibix; EGFR). Tumors overexpress antigens that may occur at earlier developmental stages of the cell. Common terms to describe such antigen expression include differentiation antigen (CD33, GD2, PSMA), tumor-testis antigen (A33), oncofetal antigen (GD2, B7H3), and driver mutation-associated antigen (HER2, CA9). There is much more to come, and, in fact, these just represent the tip of the iceberg of biologic agents that will offer new staging and diagnostic benefits in the age of precision medicine. There is great promise, even laboratory evidence [67, 68], that in the decade ahead, we shall be able to achieve therapeutic ratios of radiotargeting to tumor that are curative, even possibly for the most highly resistant solid tumors (Fig. 24)!
Table 3

Commonly used radioantibodies at MSKCC



68Ga-Fab’2 herceptin

HER2 receptor (breast, prostate, lung) [60, 61]


A33 antigen (colorectal) (see Fig. 20)


Carbonic anhydrase 9 (hypoxia, renal cell) [59]


GD2 (neuroblastoma, melanoma) [62]


B7H3 (melanoma, prostate, pediatric cancers, sarcoma) [63]


CD33 (AML, CML) [64]


PSMA (prostate, tumor vasculature) [65, 66]

Fig. 24

124I-A33 images obtained at 5 days postinjection. Protocol involved surgical sampling, which revealed an occult periaortic lymph node containing tumor. Autoradiography (a) and H&E histology (b) showing that the antibody targets the cellular component of the mass. Fusion images with PET displayed in hot body format, so that the most intense radioactivity is white and the least intense in red, overlaid onto the axial (c) and coronal (d) (Images courtesy of Jorge Carrasquillo, MD). Perhaps the most important concept illustrated by these images is the fact that radioantibody uptake is driven by antigen concentration at the tumor level (e). This has important implications, including nonlinear uptake kinetics. Another important fact derived from this study was that occupancy of the tumor receptor (A33, in this case) was in fact at 20–50% occupancy, not at tracer dose levels (From [69])


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Steven M. Larson
    • 1
  1. 1.Molecular Imaging and Therapy ServiceMemorial Sloan Kettering Cancer CenterNew YorkUSA

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