The promise of personalized medicine in cancer will only be met once physicians have both the arsenal of therapeutics they need and a more complete understanding of genomic tumor profiles. At The Wistar Institute’s Melanoma Research Center, we are using Patient-Derived Xenograft (PDX) models to create laboratory avatars for individual melanoma patients. With these avatars, we can explore and test therapeutic schemes that we can then translate back into patient care.

One of our goals is to characterize an entire PDX bank, a database that one day will allow oncologists to select the individual drug or combination therapy based on biomarkers exhibited by patients’ tumors. PDX mice also allow us to test novel drugs in the tumor grafts of patients who have relapsed during treatment, and to screen for novel drug combinations. These three projects allow us to study melanoma as it is found in patients and focus on a personalized approach to the treatment of this highly heterogeneous disease. We expect that these studies will lead to novel biomarker signatures of response for subgroups of melanoma patients and improvements in therapeutic combinations.

To create an avatar, we must first collect a sample from a patient. We graft our tumor sample underneath the skin of a NOD scid gamma (NSG) mouse. PDX yields tumors that more faithfully recapitulate the natural growth of tumors in humans, and with a higher rate of spontaneous metastases and fewer artifacts than we see in cultured cell lines.

To create a set of avatars, we need to amplify the available amount of patient tissue. To do this, we remove the growing tumor from our avatar, dice it up, and implant the diced tissue into a set of new NSG mice. We can repeat this process multiple times to create an array of avatars for a study.

This is going on right now at Wistar, with melanoma patient samples from our clinical collaborators. Wistar enjoys a historic close relationship with the University of Pennsylvania’s Abramson Cancer Center in this regard, but we have recently also established partnerships with the Helen F. Graham Cancer Center at Christiana Care, which has provided some rare tumor subtypes; the Wills Eye Institute, which has provided ocular melanoma tissue; and with Massachusetts General Hospital and MD Anderson Cancer Center, both of which are leaders in melanoma treatment.

In one example, we received a lymph node metastasis biopsy from a patient just before he was starting therapy with a BRAF inhibitor for his previously untreated stage IV BRAFV600E melanoma. Unfortunately, the patient’s best response was stable disease and he progressed after only 4 months of therapy.

After successfully establishing the patient’s tumor as xenografts, we began treating the mice with the same therapy the patient had received and saw that the tumor, again, was resistant to the BRAF inhibitor alone. We then treated another cohort of mice with the combination of a BRAF and a MEK inhibitor, a combination that since then has been shown to be superior to BRAF inhibitor single-agent therapy in clinical trials. This time, we saw tumor regression in the mouse avatars of the patient (

Figuring out the molecular mechanisms behind these differing responses is the focus of ongoing investigation, with the goal of informing future treatment decisions. Although the information derived from this experiment could not be used for the benefit of this particular patient (he never received this combination therapy), we hope to streamline the process in the future to make this kind of personalized medicine possible in melanoma.

PDX models are powerful tools for predicting a patient’s response to therapies. In time, we hope to establish a database cataloging cancer biomarkers and drug responses to upwards of 1000 PDX avatars, which will allow us to work with all subgroups of the disease and draw statistically relevant conclusions regarding their phenotypes and responses to therapy.

Of course, it can take almost a year to grow the amount of tissue we need to establish a large cohort of avatars, which limits the utility of using PDX avatars to determine individual patient therapy. On the scale of weeks, however, such avatars could help oncologists rule out proposed therapies or help choose the better of two options. The potential of creating patient avatars is immense, yet underexplored in the clinic.

		Figure. Tumor growth curve of a BRAFV600E melanoma PDX derived from a treatmentnaïve patient.

		Each treatment group consisted of 10 mice; error bars are standard error of the mean. The tumors were implanted into mice after several rounds of serial implantation to expand the original biopsy. Once tumors were established, it took 20 days to reach the maximal volume in the control group (dark blue line). When treated with a BRAF inhibitor (light blue line) no treatment effect could be observed. Interestingly, when the BRAF inhibitor was combined with a MEK inhibitor, tumors regressed in all animals (yellow line).

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The promise of personalized medicine in cancer will only be met once physicians have both the arsenal of therapeutics they need and a more complete understanding of genomic tumor profiles. 

Patient-Derived Xenograft (PDX) Models as Avatars for Patient Response to Therapy

	Assistant Professor, Department of Medicine

	Co-Leader, Genitourinary Cancers Program

	Laura and Isaac Perlmutter Cancer Center

The last major breakthrough in treatment for metastatic bladder (urothelial) cancer occurred in the 1980s, when cisplatin-based therapies, specifically MVAC (methotrexate, vinblastine, doxorubicin, and cisplatin), became the new standard of care. A major step toward improved tolerability of cisplatin-based therapy came in the early 2000s with the advent of the modern regimen of gemcitabine and cisplatin. However, the number of individuals who respond to this type of chemotherapy and the average survival have not significantly changed. More effective and better tolerated treatments remain a critical need.

Recent efforts toward the comprehensive molecular characterization of muscle-invasive urothelial bladder cancer—notably, the recent publication by The Cancer Genome Atlas (TCGA) Research Network in the journal 

 (2014;507[7492]:315-322)—have provided a detailed landscape of the varied genetic alterations in muscle-invasive urothelial cancer, giving promise to future trials of targeted therapies that may be selectively used to treat a specific patient’s tumor. With novel molecular biology dramatically opening up the field, intensified research is pointing to the identification of genetic biomarkers and better tolerated and more effective molecularly targeted therapies.

Immunomodulatory agents are also a new and promising class of treatments that present newfound optimism for the treatment of bladder cancer. First tested in patients with advanced melanoma, this class of immune-targeted therapy—more specifically, “immune checkpoint inhibitors”&mdash;also has the potential to revolutionize the treatment of advanced non— small cell lung cancer and advanced renal cell cancer, and is now being tested in advanced bladder cancer.

Bladder cancer researchers at NYU Langone Medical Center and its Laura and Isaac Perlmutter Cancer Center are working to better understand the mechanisms underlying the anticancer effect of these therapies, with the intent to help design the optimal treatment strategy for an individual patient.

As molecularly targeted therapies and immunetargeted therapies move through clinical trials, we hope to make major strides in improving the lives of patients with this devastating disease.

In June, recruitment commenced at NYU Langone and several clinical centers across the country on a multicenter, phase II, single-arm study of the immune checkpoint inhibitor MPDL3280A for advanced bladder cancer. This promising agent is a monoclonal antibody that blocks PD-L1, which is commonly expressed on bladder cancer cells, from binding to one of its receptors, PD-1, which is expressed on specific anticancer T cells. When activated, the PD-1 receptor on T cells signals an “off-switch” or “checkpoint” for these T cells, preventing its anticancer effect and allowing the bladder cancer cells to grow and invade unchecked. By blocking this interaction, we hope to reactivate the body’s own immune system against bladder cancer.

A particular strength of NYU Langone’s Perlmutter Cancer Center is the research of our dedicated laboratory, led by Xue-Ru Wu, MD, professor of Urology and Pathology, in studying bladder cancer biology in a mouse model of bladder cancer with an intact immune system.

His work using transgenic mouse models of bladder cancer has led to seminal insights into the molecular biology of bladder cancer and now serves as a unique model in which to test and better understand immune checkpoint inhibitors.

	Cell-Cycle Regulation and Bladder Cancer

A hallmark of cancer is loss of cell-cycle control, leading to unrestricted proliferation of cancer cells’ cyclin-dependent kinases (CDKs), which are enzymes that regulate the cell cycle and are over-activated in many cancers, resulting in rapid proliferation. Data from the recently published TCGA analysis of bladder cancer identified CDKs 4 and 6 as over-activated in a significant proportion of patients with bladder cancer. Specific CDKs are only active during certain parts of the cell cycle, making careful pinpointing of pharmacokinetics, dosing, and targeting of compounds essential. Agents that selectively block both CDKs, potentially arresting growth of a cancer cell before it can replicate its DNA, are actively under study. Two small molecule inhibitors of CDK 4 and 6 show tremendous promise: PD-0332991 and LEE001 will be investigated in advanced bladder cancer in the near future.

Another exciting avenue of research involves genes that regulate chromatin, the complex of DNA and its supporting proteins, histones, and the native form of the genetic material within the cell’s nucleus.

The tightly compact interaction of histones with DNA serves to “silence” specific genes from being expressed, and chromatin remodeling genes alter or open this interaction to allow genes to be expressed.

Mutations in key regulators of chromatin remodeling, namely MLL2, ARID1A, and KDM6A, were discovered in nearly 90% of all bladder cancers analyzed by the TCGA. While research has not yet identified the optimal way to target these mutations, histone deacetylase (HDAC) inhibitors, DNA methyltransferase inhibitors, and bromodomain inhibitors may hold promise in the future.

Receptor tyrosine kinases (RTKs) expressed on the surface of cancer cells, and in the enzymes inside the cancer cell that are linked to specifc RTKs, are well known to be commonly mutated in a variety of cancers. These mutations typically lead to uncontrolled cell signaling, proliferation, and cancer-cell invasion. Once again, the TCGA analysis identified a number of previously known mutations and a few novel mutations in specific components of these pathways, including ERBB2, FGFR3, and the PI3-kinase/AKT/mTOR pathway. A number of new compounds targeting these pathways, which are more potent and selective, are currently in development.

Combined with a better understanding of the molecular biology of bladder cancer, these new compounds provide hope for the identification of an effective treatment for specific subsets of bladder cancer patients.

While we are still in the early stages of understanding the therapeutically relevant molecular biology of bladder cancer, recent breakthroughs in molecular characterization efforts, such as the TCGA analysis, as well as in the arena of immunotherapy, provide great promise for the future of bladder cancer treatment. It is painstaking work that must be done carefully. We remain optimistic that further scientific study will lead to the development of better tolerated and more effective treatments and, in doing so, improve survival for patients with bladder cancer.

A major step toward improved tolerability of cisplatin-based therapy came in the early 2000s with the advent of the modern regimen of gemcitabine and cisplatin.

Molecularly Targeted Therapy and Immunotherapy: The Next Frontier in Metastatic Bladder Cancer

A genomic analysis of renal cell carcinoma (RCC) has uncovered new clues about the development, growth, and spread of the cancer.

The analysis, which was published online June 12 in the journal 

, targeted the clear-cell form of the disease, which comprises 80% of cases, and found 31 genes that are key in causing and spreading the cancer. Eight of the genes had not previously been linked to renal cancer, and six others were not previously linked to any cancer, according to a press release from the Mayo Clinic News Network.

Mayo described the analysis as the most extensive to date on the role of gene expression in clear-cell RCC (ccRCC). “The power of this study is that we looked at genes discovered to be overexpressed in patients’ tumors and determined their function in kidney cancer, which has not been done on a large scale before,” the study’s senior investigator, molecular biologist John A. Copland, PhD, stated in the press release. “This is a seminal step in identifying key pathways and molecules involved in kidney cancer so that specific therapies that target these new genes can be developed to treat this cancer.”

While the prognosis for kidney cancer that has not spread is good, patients with advanced or metastatic disease will develop drug resistance. Those with untreated metastatic disease have a 5-year overall survival rate of <10%, according to the release.

“We are releasing these discoveries to the scientific community so that a large effort can be mounted to find out more about these genes and how they can be effectively targeted,” Copland said. “We owe patients speedy research that focuses on new treatments to save lives.” New treatments might be less toxic than existing targeted therapies for the disease, he added.

The investigators found the relevant genes by comparing samples of tissue with and without kidney cancer (72 samples each) and looking for under-or-overexpression of RNA and protein production in the samples with cancer. In a high-throughput genetic analysis coupled with a high-throughput proliferative screen, they found about 6000 genes of interest, then isolated and tested 195 that were consistently elevated in patient samples. Finally, the researchers tested the genes in living cancer cells to see if they contributed to the growth or spread of disease; that reduced their list to 31 genes required for ccRCC cell propagation.

“We also found genes with other functions that are key to kidney cancer survival, such as inflammation. Another found gene is linked to angiogenesis…This is a novel discovery,” said Mayo Clinic graduate student and lead study author Christina von Roemeling. “It is particularly important because ccRCC is well known for being a very angiogenic cancer.”

In addition to angiogenesis, many of the isolated genes are implicated in metabolism, differentiation, and cell motility in other cancer systems, the authors wrote in their paper. “Of these, we further establish a role for CDH13 in tumor angiogenesis, as well as a promigratory role for four novel factors, including KISS1R, KSR1, CAMK1, and SSPN in ccRCC,” they wrote. Little is known, so far, about the protein function of several of these gene products, they noted. Von Roemeling agreed that the findings will have important research implications.

“In addition to the potential of these genes and gene products to help us design new drugs, they could also serve as biomarkers for accurate diagnosis,” she said in the press release. “It really is a treasure trove for future research on kidney cancer.”

Genes That Drive Clear-Cell RCC Discovered, Providing Research Clues

		Lymphoma Division Chief John Theurer Cancer Center at HackensackUMC

		Chief Science Officer and Director of Research and Innovation Regional Cancer Care Associates

, a very critical paper appeared reporting on a study conducted as part of The Cancer Genome Atlas (TCGA).

This is the largest study of its kind to date, looking at molecular and genetic characteristics of more than 3500 tumor samples of 12 different cancer types using a multi-platform approach. This is important since previous molecular studies have mostly focused on 1 technology at a time and on pathologically defined tumor types identified as ‘‘within-a-tissue/ organ’’ disease subtypes.

This new approach looked at comprehensive genomics using 6 different platforms— mostly genomics such as DNA and RNA sequencing, plus a protein expression profiling.

An extensive bioinformatics analysis was then performed across all platforms to identify subgroups with similarities (clusters), which led to defining distinct molecular subtypes of cancer (different pathways). A total of 11 cancer types were identified, which provided independent and clinically relevant prognostic information above and beyond tumor stage and primary tissue-of- origin. Based on this study, 1 in 10 cancer patients would be classified differently by this new molecular taxonomy versus our current tissue-of-origin tumor classification system.

This is obviously potentially relevant for the management of these patients (particularly in the era of novel targeted therapies), since the proportion of potentially misclassified tumors is comparable to the rate of EGFR mutations in unselected non—small cell lung cancers (treated with radically different therapy).

Also in the study, the divergence of cancer within one subtype or the overlap among different cancers (from different organs) was provocative. For example, at least three subtypes of bladder cancer were identified with different outcomes; one of these subtypes was virtually indistinguishable from lung adenocarcinomas, and another was most similar to squamous cell cancers arising from head-and-neck tumors.

The research highlighted and confirmed known differences between subtypes of breast cancer, but also revealed the new and surprising finding that basal-like breast cancers actually constitute their own cancer class. Basal-like breast cancers, which are commonly referred to as triple-negative breast cancers, are particularly aggressive and more prevalent among African-American and younger women. At the molecular level, these basal-like breast cancers might have more in common with ovarian cancers and cancers of squamous cell origin than with other subtypes of breast cancer.

Though obviously this still needs validation, the potential of these data is nothing less than revolutionary—as the number of cases studied increases (reflecting more of the cancer diversity), the authors of the Cell paper suggest that up to 30% to 50% of cases might eventually be reclassified! The new classification approach may (should) shift the field to focus more on the development of drugs targeting larger groups of cancers with genomic similarities, as opposed to a single tumor type. We should be thankful to this remarkable work, which will no doubt challenge our views…I believe for the better.

	Hoadley KA, Yau C, Wolf DM, et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin [published online August 7, 2014]. Cell. doi:10.1016/j.cell.2014.06.049.

A disruptive study challenges our current system in classifying
cancer. Will a new molecular taxonomy of tumors arise and
change our views on patient management?

August 2014 | Oncology & Biotech News

Patient-Derived Xenograft (PDX) Models as Avatars for Patient Response to Therapy

Molecularly Targeted Therapy and Immunotherapy: The Next Frontier in Metastatic Bladder Cancer

Genes That Drive Clear-Cell RCC Discovered, Providing Research Clues

A Revolution in Classifying Cancer?