Harnessing Cell Signaling to Treat Cancer: The 2015 Ross Prize in Molecular Medicine

Journal Articles

Auger KR, Carpenter CL, Cantley LC, Varticovski L. Phosphatidylinositol 3-kinase and its novel product, phosphatidylinositol 3-phosphate, are present in Saccharomyces cerevisiae. J Biol Chem. 1989;264:20181-4.

Baselga J. Bringing precision medicine to the clinic: from genomic profiling to the power of clinical observation. Ann Oncol. 2013;24:1956-7.

Berry DA. The Brave New World of clinical cancer research: adaptive biomarker-driven trials integrating clinical practice with clinical research. Mol Oncol. 2015;9:951-9.

Bosch A, Li Z, Bergamaschi A, et al. PI3K inhibition results in enhanced estrogen receptor function and dependence in hormone receptor-positive breast cancer. Sci Transl Med. 2015;283ra51.

Cantley LC. Cancer, metabolism, fructose, artificial sweeteners, and going cold turkey on sugar. BMC Biol. 2013;12:8.

Coates AS, Winer EP, Goldhirsch A, et al. Tailoring therapies-improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer. Ann Oncol. 2015. [Epub ahead of print]

Cussenot O, Cancel-Tassin G. Precision medicine in oncology needs to integrate pharmacogenetic profiling. Eur Urol. 2015. [Epub ahead of print]

Damodaran S, Berger MF, Roychowdhury S. Clinical tumor sequencing: opportunities and challenges for precision cancer medicine. Am Soc Clin Oncol Educ Book. 2015;35:e175-82.

Deluche E, Onesti E, Andre F. Precision medicine for metastatic breast cancer. Am Soc Clin Oncol Educ Book. 2015;35:e2-7.

Elkabets M, Vora S, Juric D, et al. mTORC1 inhibition is required for sensitivity to PI3K p110α inhibitors in PIK3CA-mutant breast cancer. Sci Transl Med. 2013;5:196ra99.

Emerling BM, Hurov JB, Poulogiannis G, et al. Depletion of a putatively druggable class of phosphatidylinositol kinases inhibits growth of p53-null tumors. Cell. 2013;155:844-57.

Fruman DA, Cantley LC. Idelalisib: a PI3Kδ inhibitor for B-cell cancers. N Engl J Med. 2014;370:1061-2.

Gallop JL, Walrant A, Cantley LC, Kirschner MW. Phosphoinositides and membrane curvature switch the mode of actin polymerization via selective recruitment of toca-1 and Snx9. Proc Natl Acad Sci U S A. 2013;110:7193-8.

González-Billalabeitia E, Seitzer N, Song SJ, et al. Vulnerabilities of PTEN-TP53-deficient prostate cancers to compound PARP-PI3K inhibition. Cancer Discov. 2014;4:896-904.

Graziani A, Ling LE, Endemann G, et al. Purification and characterization of human erythrocyte phosphatidylinositol 4-kinase. Phosphatidylinositol 4-kinase and phosphatidylinositol 3-monophosphate 4-kinase are distinct enzymes. Biochem J. 1992;284 (Pt 1):39-45.

Hyman DM, Diamond EL, Vibat CR, et al. Prospective blinded study of BRAFV600E mutation detection in cell-free DNA of patients with systemic histiocytic disorders. Cancer Discov. 2015;5:64-71.

Juric D, Castel P, Griffith M, et al. Convergent loss of PTEN leads to clinical resistance to a PI(3)Kα inhibitor. Nature. 2015;518:240-4.

Klempner SJ, Myers AP, Cantley LC. What a tangled web we weave: emerging resistance mechanisms to inhibition of the phosphoinositide 3-kinase pathway. Cancer Discov. 2013;3:1345-54.

Lloyd MC, Rejniak KA, Brown JS, et al. Pathology to enhance precision medicine in oncology: lessons from landscape ecology. Adv Anat Pathol. 2015;22:267-72.

Locasale JW, Cantley LC. Metabolic flux and the regulation of mammalian cell growth. Cell Metab. 2011;14:443-51.

Mandrekar SJ, Dahlberg SE, Simon R. Improving clinical trial efficiency: thinking outside the box. Am Soc Clin Oncol Educ Book. 2015;35:e141-7.

Mayer IA, Abramson VG, Isakoff SJ, et al. Stand up to cancer phase Ib study of pan-phosphoinositide-3-kinase inhibitor buparlisib with letrozole in estrogen receptor-positive/human epidermal growth factor receptor 2-negative metastatic breast cancer. J Clin Oncol. 2014;32:1202-9.

Menon S, Dibble CC, Talbott G, et al. Spatial control of the TSC complex integrates insulin and nutrient regulation of mTORC1 at the lysosome. Cell. 2014;156:771-85.

Redig AJ, Jänne PA. Basket trials and the evolution of clinical trial design in an era of genomic medicine. J Clin Oncol. 2015;33:975-7.

Ruderman NB, Kapeller R, White MF, Cantley LC. Activation of phosphatidylinositol 3-kinase by insulin. Proc Natl Acad Sci U S A. 1990;87:1411-5.

Schwartz S, Wongvipat J, Trigwell CB, et al. Feedback suppression of PI3Kα signaling in PTEN-mutated tumors is relieved by selective inhibition of PI3Kβ. Cancer Cell. 2015;27:109-22.

Serunian LA, Cantley LC. Growth factor and oncogene influences on cell growth regulation. Ann NY Acad Sci. 1988;551:309-19.

Shaywitz AJ. PI3K enters beta-testing. Cell Metab. 2008;8:179-81.

Soltoff SP, Carpenter CL, Auger KR, et al. Phosphatidylinositol-3 kinase and growth regulation. Cold Spring Harb Symp Quant Biol. 1992;57:75-80.

Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009;324:1029-33.

Wong KK, Engelman JA, Cantley LC. Targeting the PI3K signaling pathway in cancer. Curr Opin Genet Dev. 2010;20:87-90.

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PI3K, lynchpin of a master signaling network

The phosphoinositide 3-kinase (PI3K) signaling pathway is the mechanism through which insulin regulates blood glucose levels and a major player in up to 80% of human cancers. Almost 30 years after Lewis Cantley discovered the enzyme, and after almost 20 years of research establishing its link to cancer, PI3K is now a clinical target. A PI3K inhibitor received approval in 2014 as a treatment for B-cell lymphoma, and dozens more are in clinical trials for many types of cancer. The body of work on the PI3K pathway has placed Cantley among the top 1% of most cited authors in three fields—molecular biology and genetics, biology and biochemistry, and clinical medicine.

First observed by Cantley as a lipid-phosphorylating enzyme often found among oncoproteins that cause cancer in mice and chickens, PI3K was soon recognized as a new species of phosphoinositides, designated as such on the basis of the position at which the enzyme adds phosphate molecules to the inositol ring on lipids. Cantley further observed that not only was the lipid produced by PI3K (called PIP3) found at very high levels in cancers, but its levels, which reflected PI3K activity, correlated with cells' ability to become malignant and to cause tumors in mice.

The PI3K and PTEN pathways are mutually antagonistic, respectively promoting and preventing cancer signaling. (Image courtesy of Lewis C. Cantley)

More than a decade later, other groups showed that the PTEN gene acts as a counterweight to PI3K activity, by producing a phosphatase that removes phosphates from the same lipid to which PI3K adds these molecules. PTEN thus acts as a tumor suppressor in a network where PI3K acts as an oncogene.

Recognizing that PI3K did not evolve to cause cancer, Cantley investigated its function in normal cells, finding this enzyme and its lipid-phosphorylating activity only in multicellular organisms, where it is regulated by insulin and insulin-like growth factors. PI3K is the decision-making mechanism that allows multicellular organisms to regulate anabolic growth, the process by which tissues take up nutrients such as glucose to grow at specific times and to specific sizes during development. Under normal conditions, pathways for tissue growth that are turned on by PI3K are tempered by PTEN, the braking system that ensures controlled growth.

It is now known that four genes encode enzymes that produce PIP3: PIK3CA, CB, CD and CG. Only the PIK3CA gene, which mediates insulin signaling, is highly mutated in human cancer. In cancer, mutations in PTEN or PI3K genes, or persistent activation of PI3K by insulin, growth factors, or hormones, keep the system turned on continuously, resulting in high lipid production levels and rapid and continuous tissue growth. Subsequently, the tissues expand, with the new cells spilling out of the predetermined boundaries. Thus these processes can also lead to tissue growth outside the main organ, producing subsequent metastatic disease.

Cantley and others have uncovered all the major members of the PI3K network, notably mTOR and Raptor, which constitute an important downstream node. The network has been shown to be sensitive to changes in glucose levels, amino acid levels, stress, and the availability of growth factors. There are redundancies among the pathways in the network—mainly between the PI3K and MAPK signaling cascades, which both control mTOR activity. Thus drugs that block the MAPK pathway would be unlikely to inhibit signaling through the PI3K pathway, and vice versa.

PI3K is the lynchpin of a vast network with redundant signaling pathways that have made it challenging to block PI3K-driven signaling with inhibitors targeted at specific proteins in the pathway. (Image courtesy of Lewis C. Cantley)

The PI3K network is analogous to a computer's logic AND gate: network activation and the resulting tissue growth are dependent on three conditions—detection of a growth factor, availability of sufficient essential amino acids to build cellular protein, and availability of ATP to power biochemical reactions. Under normal conditions, the absence of any of these conditions would prevent growth. Cancer occurs because there are "breaks in the logic" or defects in the network that allow cellular growth even in the absence of one or more of these conditions.

Advances in human genome sequencing over the past 5 years have helped scientists establish that PI3K network mutations are second only to RAS mutations as the dominant oncogenes in most tumors. Up to 70% of cancer types with high mortality rates have frequent mutations in at least two dozen genes in this network. Cantley has been particularly interested in women's cancers, such as uterine, cervical, breast, and ovarian, which often have high rates of activating point mutations in PI3KCA or amplifications that increase the copy number of this gene. These cancers have become a focus of his efforts in drug development against PI3K.

The Cancer Genome Atlas project sequenced DNA from cancers found in women, such as uterine, ovarian, breast, and cervical cancer, and showed that the PI3KCA gene is mutated at very high frequency in these cancers. (Image courtesy of Lewis C. Cantley)

Speaker:
Lewis C. Cantley, Weill Cornell Medical College

Highlights

• Not all patients who harbor a PI3KCA mutation respond to treatment with an inhibitor targeted at that mutation. A better way to predict the response is to measure glucose uptake, a marker for cancer cell metabolism, via the imaging technology FDG-PET. A decrease in a tumor's glucose metabolism correlates with a clinical response to therapy.
• In mouse tumors, the potency of a PI3KCA inhibitor is dramatically increased by combining it with a PARP inhibitor to enhance DNA damage in cancer cells; a clinical trial is now underway to test this combination in humans.
• PI3K signaling activates the cell's actin cytoskeleton and triggers the release of aldolase, an enzyme that promotes the production of DNA nucleotides. Combining a PI3KCA inhibitor with a PARP inhibitor, which prevents the repair of damaged DNA, thus enhances DNA damage in cancer cells and promotes tumor shrinkage.

Identifying responders to anti-PI3K therapy

The anti-PI3K candidate drugs currently in clinical trials include some that are specific for one of the PI3K enzymes, such as PIK3CA or PIK3CB, and one pan-PIK3K inhibitor. The only approved PI3K drug, idelalisib, targets PIK3CD, which directs cell growth in B cells but not in T cells. Hence the drug is of benefit in B-cell cancers like chronic lymphocytic leukemia (CLL) but not in T-cell leukemias.

In his presentation after the prize ceremony, Lewis C. Cantley of Weill Cornell Medical College described his current work to expand the use of PI3K inhibitors. With funding from American Association of Cancer Research and Stand Up To Cancer, Cantley partnered with researchers at five other institutions to design trials to identify which patients would benefit from PI3K inhibitors used alone or in combination with other drugs.

In a phase I trial of a PI3KCA inhibitor called BYL719, in which all 72 patients had a PIK3CA mutation, not all patients benefitted from treatment. A majority of patients whose tumors did not shrink after BYL719 treatment had colorectal cancer; in addition to PI3KCA mutations, they harbored mutations in KRAS, a driver oncogene in the MAPK pathway.

Because PI3K mutations alone did not prove to be a foolproof way to identify patients who would respond to treatment, Cantley began to explore the idea of using glucose uptake—a indicator of cancer cell metabolism—as a marker of drug response. This idea stems from the discovery by Otto Warburg, in the 1950s, that cancers metabolize glucose through glycolysis at rate that is up to 200 times higher than the rate seen in normal tissues. This principle underlies the imaging technology FDG-PET (fluorodeoxyglucose positron emission tomography) that is used to visualize tumors in the clinic today.

Cantley's team showed using FDG-PET that lung tumors in mice driven by PI3KCA mutations had high glucose consumption that decreased to normal levels within 48 hours of treatment with PI3K inhibitor. The tumors shrank after less than a week of treatment. The change in glucose uptake correlated with tumor sensitivity to the drug: treating the mice with inhibitors of AKT, another protein in the PI3K network, had no effect on glucose metabolism or tumor size, probably because of a redundancy in this signaling network.

A phase Ib clinical trial recently published in the Journal of Clinical Oncology has confirmed that these findings translate to humans. The trial found a strong correlation between a significant decrease in glucose uptake seen via PET within 48 hours and a clinical response (tumor shrinkage) occurring up to 2 weeks later. Larger trials are now underway. One goal is to be able to use PET results to quickly determine whether a patient is on the right therapy.

A phase I trial showed a strong correlation between decreased tumor metabolism (blue and dark yellow) and clinical response (green, pink, light yellow). In contrast, a patient's PI3KCA mutational status (orange) showed weak or no correlation with clinical response. (Image courtesy of Lewis C. Cantley)

The preclinical mouse experiments also suggested a second line of inquiry in patients with triple negative breast cancer (TNBC), whose mutational profile resembles that of ovarian cancer but not of other breast cancer subtypes. Cantley found that TNBC patients are highly likely to have lost PTEN tumor-suppressor activity and often carry mutations in BRCA, p53, PI3KCA, AKT1, and other genes.

In engineered mice with deletions in BRCA and p53 in breast tissue, untreated tumors grew very quickly—doubling in size every 16 days and killing the mice within a week. Although mice treated with PI3KCA inhibitors had reduced glucose metabolism within 48 hours, most failed to survive beyond a month.

Cantley's team therefore turned to testing combination regimens. Tumor cells in the mice showed above-normal DNA damage, so the team added a second drug to block DNA damage repair. The second drug, a PARP inhibitor, increased the activity of the PI3KCA inhibitor—increasing the level of DNA damage. The combination therapy resulted in tumor cell death, and the mouse tumors shrunk dramatically. In a different set of experiments by José Baselga at Memorial Sloan-Kettering Cancer Center, the same drug combination produced similar results in mice with human TNBC tissue grafted onto mouse fat pads.

Encouraged by these results, Cantley sought a partnership with the pharmaceutical manufacturers of the drugs. A subsequent phase I study tested the combination in 70 ovarian and breast cancer patients who had previously failed other standard therapies. The results, presented at the American Association for Cancer Research 2015 annual meeting, demonstrated that a majority of the patients showed a robust response to the PI3KCA inhibitor and PARP inhibitor combination. Some patients are still enrolled in the trial after 3 years, and a phase II trial is ongoing.

A majority of breast and ovarian cancer patients enrolled in a phase I trial experienced a significant decrease in tumor lesion size when treated with a combination regimen of a PI3KCA inhibitor and a PARP inhibitor. (Image courtesy of Lewis C. Cantley)

Investigating the biochemistry: why does the combination work?

Cantley's team also investigated how the PI3KCA inhibitor and PARP inhibitor combination alters tumor metabolism. They found that PI3K inhibition dramatically reduced within 24 hours cellular levels of the four deoxynucleotide triphosphates (dNTPs)—the DNA bases A, T, G, and C—which are required for DNA synthesis. The resulting increase in DNA damage ultimately killed the cells. In contrast, the cells had no significant changes in the levels of components required for RNA and ATP synthesis.

The dNTPs are synthesized via glucose metabolism that is regulated by the PI3K/AKT signaling pathway. But after finding that dNTP levels decreased only in response to PI3KCA inhibitors, not AKT inhibitors, Cantley's team examined the glycolysis pathway more closely to identify the point at which PI3K signaling diverges from AKT signaling.

They identified the enzyme aldolase, a component of the glycolytic pathway that is inhibited by PI3KCA inhibitors but not by AKT inhibitors. It had been known since the 1970s that aldolase is mostly trapped in the actin cytoskeleton of quiescent cells; activating the cells through PI3K signaling, a response to growth factors or other signals, mobilizes actin and releases aldolase. AKT signaling, they found, has no effect on actin, and hence does not activate aldolase.

The combination of the PI3KCA and PARP inhibitors exerts greater DNA damage than either agent alone as a result of the blocking of the release of aldolase (ALDOA), an enzyme that is required for the synthesis of new DNA molecules (dNTPs). (Image courtesy of Lewis C. Cantley)

Tested in vivo, in mouse tumors with mutations in p53 and BRCA genes, PI3KCA inhibitors stopped glycolysis and reduced aldolase levels, and consequently dNTP levels, leading to massive DNA damage and tumor cell death.

Experiments like this one, aimed at understanding both the clinical consequences of targeting the PI3K network and the biochemistry that drives cellular responses to PI3K inhibitors, help researchers determine how best to use targeted drugs to treat solid tumors.

Speaker:
José Baselga, Memorial Sloan-Kettering Cancer Center

Highlights

• Basket trials are a new strategy to find drugs to which a patient's cancer will respond, screening patients by tumor genotype (mutation profile) rather than by cancer type. The trial design is flexible enough to allow protocol modifications and to study new drug combinations on the basis of new information about a patient's tumor status.
• Drugs that target specific mutations in a tumor put selective pressure on the tumor, forcing it to evolve by switching to a different mutational pathway to drive its growth, leading to drug resistance. Tracking tumor evolution during therapy could help pinpoint such changes as they occur, allowing researchers to modify treatment by adding new drugs to target emerging mutations and thereby prevent tumor escape.

The promise of precision medicine

The National Cancer Institute (NCI) defines precision or personalized medicine as the use of information about a person's genes, proteins, and environment in the prevention, diagnosis, and treatment of disease. José Baselga, chief medical officer at Memorial Sloan-Kettering Cancer Center (MSKCC), outlined a vision for precision medicine in simple terms: to match each patient's tumor with appropriate combinations of therapy.

Precision medicine in cancer treatment will involve genotyping a patient's tumor to identify driver mutations, selecting a regimen on the basis of the tumor genotype, and monitoring response to treatment in real time during therapy rather than at long intervals after initiating therapy. (Image courtesy of José Baselga)

Precision medicine in oncology informs the spectrum of treatment and research activities, including the identification of genetic aberrations that drive tumor growth in patients and the design of clinical trials tailored to patients' mutational profiles. Baselga pointed to advances in tumor genotype analysis and in real-time monitoring of tumor response to therapy as particularly helpful for these efforts.

The NCI and the National Institutes of Health (NIH) are supporting a project at MSKCC and other institutions to define the landscape of mutations seen in different types of cancer. This work has generated a tremendous amount of data that oncologists are using to define tumors by mutational profile and to inform treatment decisions. Not all mutations identified in a particular tumor are drivers of the cancer; some are so-called passenger or bystander mutations. Researchers are only beginning to understand the significance of these passenger mutations, which may modify sensitivity to therapy or influence its outcome, or modify tumor behavior.

At MSKCC, Joan Massagué is spearheading a functional genomics initiative that aims to validate findings from clinical sequencing and to further define the mechanisms by which passenger mutations exert their effects. More work is also needed on driver mutations. Although much is known about mutations in BRCA in breast cancer and in AKT, Erbb2, and PI3K in many other cancers, and about their role in cancer growth, no therapies directly targeting such driver mutations are approved for clinical use.

New paradigms in cancer therapeutic development: basket trials and real-time monitoring

To advance clinical development, researchers are analyzing mutations, searching for correlations in response to therapy between phase I and phase III trials (which provide stronger evidence of efficacy), conducting trials targeting known driver mutations, and investigating how mutational heterogeneity within tumors evolves in response to therapy and how these changes lead to drug resistance.

One clinical research strategy is the basket clinical trial, in which patients are chosen by their mutation type rather than their cancer type. The idea is to find drugs that target driver mutations in any type of cancer and to be able to predict a response to therapy on the basis of a mutation or molecular marker, independent of tumor histology.

A basket trial design example in which patients with the BRAF mutation are enrolled regardless of their tumor type (lung, melanoma, etc.) and assessed for response to a BRAF inhibitor vemurafenib. (Image courtesy of José Baselga)

This type of trial design incorporates 15–20 patients per arm and allows researchers to conduct what amounts to several parallel phase II trials for one drug across different types of cancer. The genotypic alterations of interest are typically present at low frequency in different tumor types, and researchers define a priori a response threshold that would classify a drug as a worthwhile therapy for a particular tumor type.

Baselga described a basket trial that will soon be published in the New England Journal of Medicine. It focused on the BRAF mutation, which drives melanoma and determines sensitivity to the drug vemurafenib, approved only for metastatic melanoma. The trial enrolled 123 patients with advanced or metastatic solid tumors other than melanoma, such as histiocytic, non-small cell lung, breast, ovarian, brain, and colorectal cancer, or a hematological cancer such as multiple myeloma. The BRAF inhibitor induced significant and impressive antitumor responses in a majority of patients across all the tumor types, with responses lasting more than a year with minimal side effects.

In some colorectal cancer patients who did not respond to the BRAF inhibitor, the addition of a second drug, cetuximab, which targets the EGFR mutation that is known to override the BRAF mutation, induced significant antitumor responses. A major advantage of the basket design is its flexibility: researchers can quickly modify the study protocol on the basis of new information about patients' tumors and study new drug combinations. With results from the BRAF inhibitor trial, researchers are seeking approval for vemurafenib in several new cancer types for patients with the BRAF mutation.

Several basket trials are underway, many targeting well-known driver mutations such as AKT, EGFR, PI3K, and others. Following these first-generation trials are second-generation trials that aim to find cancers that will respond to therapeutic combinations targeting multiple driver mutations. Enrolling patients with the specific mutations of interest could be difficult, so the major academic institutions have begun building vast genomic databases for cancer patients with whole genome and exome sequencing.

Baselga reported that MSKCC has, for example, sequenced a panel of 410 genes in more than 12 000 patient tumors in the past 2 years, as part of its MSK-IMPACT program. Of the 468 breast cancer patients sequenced, 65% have mutations in genes that can be targeted, such as PIK3CA and AKT1. Basket trials to investigate whether these tumors respond to PI3K inhibitors or AKT1 inhibitors have yielded promising results and high response rates.

Advances in next-generation sequencing technology have driven projects such as MSK-IMPACT, which has assembled the mutational landscape in hundreds of breast cancer patients, identifying the most common ones for further study in clinical trials. (Image courtesy of José Baselga)

Researchers are also exploring real-time response monitoring, which provides a more accurate picture of drug efficacy than conventional monitoring that is usually conducted after patients have received multiple lines of therapy. Real-time monitoring of cell-free tumor DNA in the blood removes the need to biopsy tumors and the uncertainty that stems from tumor heterogeneity; a tumor's mutational profile at one biopsied site might not reflect that of the whole tumor.

Real-time monitoring can inform drug trials and help researchers predict which patients will respond to therapy. In the AKT1 inhibitor MSKCC trial, for example, real-time monitoring revealed a large drop in tumor DNA in blood samples by day 4 in patients who went on to show an antitumor response at the trial's endpoint. Baselga explained that the hope is to soon enroll patients on the basis of blood mutational profiling rather than biopsied tissue sequencing.

Tracking tumor evolution to tackle drug resistance

One obstacle to successful cancer treatment is selection pressure, under which a tumor mutates in response to a drug therapy. Selection pressure can accelerate tumor growth and spur the development of drug resistance. Because most cell signaling incorporates redundant pathways, there are multiple ways for cancer cells to bypass the blockade or inhibition of a particular drug target.

Baselga and his colleagues have studied this phenomenon in patients who first respond to a drug and later develop resistance by sequencing the exomes of new and primary lesions, responding lesions, and metastasizing lesions. The group studied tumor genomic evolution in a patient with metastatic breast cancer with an activating PI3KCA mutation who initially responded to the PI3KA inhibitor BYL719 but later developed resistance and experienced metastasis of tumors to the lung. By comparing the exome sequence of the primary tumor before treatment to sequences derived from sites that were and were not responding to the drug at the time of death, the team found that all the nonresponding tumor lesions had fewer copies than normal of the PTEN tumor suppressor gene as well as genetic alterations within this gene that suppressed its function. The study was published in Nature earlier this year.

Tracking tumor evolution in a breast cancer patient who stopped responding to a PI3KCA inhibitor showed progressive loss of the PTEN tumor suppressor function, which caused the tumor to metastasize. (Image courtesy of José Baselga)

The team found similar patterns of evolution in six more breast cancer patients treated with BYL719: loss of PTEN and absence of PI3KCA mutations initially detected at the primary tumors in the post-treatment lesions. In preclinical models, they researchers discovered that PTEN loss in tumors harboring the PI3KCA mutation (and therefore sensitive to BYL719) triggered resistance to BYL917 that could only be reversed by also blocking PI3K p100beta, which activates a signaling pathway parallel to PI3KCA.

It is impractical to design drugs to target the whole PI3K network, but identifying signaling nodes that can be influenced by two or three drugs could be highly effective. In the example above, previously resistant tumors disappeared after the simultaneous blockade of both PI3K pathways, suggesting that real-time knowledge of tumor evolution could improve the effectiveness of personalized medicine.

Baselga acknowledged that tumor genetic information alone will not be sufficient to inform combinatorial design or delivery of precision medicine. Conceptual frameworks will be needed to account for both functional data from preclinical systems and genomic data from drug-sensitive and drug-resistant tumors. Robust network models are needed to deal with complex drug resistance and define how inhibition of various network components induces cell death.