Moving molecular targeted drug therapy towards personalized medicine: issues related to clinical trial design

Guidelines for clinical evaluation of anti-cancer drugs

Clinical studies intended for regulatory approval must demonstrate the clinical benefits of the drug in a target population. Clinical development of a drug proceeds by stepwise clinical studies; after safety and pharmacokinetics are evaluated and the recommended dosage and administration are determined, efficacy and safety are evaluated in an exploratory manner, and finally clinical benefits are compared with conventional standard therapies. Guidelines for the clinical evaluation of anti‐cancer drugs in Japan were established in 1991 and amended in 2006 after molecular‐targeted drugs were introduced. Recent progress in the development of drugs acting on the immune system and cancer genomic medicine targeting rare but important molecular subtypes have altered the strategy for development of anti‐cancer drugs. It is often difficult to conduct a confirmatory randomized controlled study using overall survival as the primary endpoint in rare molecular subtypes, and the primary evaluation of the efficacy of some drugs and subsequent approval is based on the tumor response. As conducting clinical studies for rare subtypes solely within Japan is difficult, drug development needs to be conducted within a global study. However, this requires robust monitoring to detect possible ethnic differences in pharmacokinetics and drug efficacy. Development using the conditional approval system for drugs enforced in 2020 may be considered, when clinical utility is evaluated based on surrogate endpoints. Because of these changes, we have revised the guidelines for the clinical evaluation of anti‐cancer drugs in Japan. To promote global development of anti‐cancer drugs involving Japan, the guidelines have been translated into English.

Recent progress in development of drugs acting on the immune system and cancer genomic medicine targeting rare but important molecular subtypes have altered the strategy for development of anti‐cancer drugs. As conducting clinical studies for rare subtypes solely within Japan is difficult, drug development needs to be conducted within a global study with monitoring possible ethnic differences. Because of these changes, we have revised the guidelines for the clinical evaluation of anti‐cancer drugs in Japan.

Identification of pharmacodynamic biomarkers and common molecular mechanisms of response to genotoxic agents in cancer cell lines

PURPOSE

Genotoxic agents (GAs) including cisplatin, doxorubicin, gemcitabine, and topotecan are often used in cancer treatment. However, the response to GAs is variable among patients and predictive biomarkers are inadequate to select patients for treatment. Accurate and rapid pharmacodynamics measures of response can, thus, be useful for monitoring therapy and improve clinical outcomes.

METHODS

This study focuses on integrating a database of genome-wide response to treatment (The NCI Transcriptional Pharmacodynamics Workbench) with a database of baseline gene expression (GSE32474) for the NCI-60 cell lines to identify mechanisms of response and pharmacodynamic (PD) biomarkers.

RESULTS AND CONCLUSIONS

Our analysis suggests that GA-induced endoplasmic reticulum (ER) stress may signal for GA-induced cell death. Reducing the uptake of GA, activating DNA repair, and blocking ER-stress induction cooperate to prevent GA-induced cell death in the GA-resistant cells. ATF3, DDIT3, CARS, and PPP1R15A appear as possible candidate PD biomarkers for monitoring the progress of GA treatment. Further validation studies on the proposed intrinsic drug-resistant mechanism and candidate genes are needed using in vivo data from either patient-derived xenograft models or clinical chemotherapy trials.

Proximity proteomics identifies cancer cell membrane cis-molecular complex as a potential cancer target

Cancer‐specific antigens expressed in the cell membrane have been used as targets for several molecular targeted strategies in the last 20 years with remarkable success. To develop more effective cancer treatments, novel targets and strategies for targeted therapies are needed. Here, we examined the cancer cell membrane‐resident “cis‐bimolecular complex” as a possible cancer target (cis‐bimolecular cancer target: BiCAT) using proximity proteomics, a technique that has attracted attention in the last 10 years. BiCAT were detected using a previously developed method termed the enzyme‐mediated activation of radical source (EMARS), to label the components proximal to a given cell membrane molecule. EMARS analysis identified some BiCAT, such as close homolog of L1 (CHL1), fibroblast growth factor 3 (FGFR3) and α2 integrin, which are commonly expressed in mouse primary lung cancer cells and human lung squamous cell carcinoma cells. Analysis of cancer specimens from 55 lung cancer patients revealed that CHL1 and α2 integrin were highly co–expressed in almost all cancer tissues compared with normal lung tissues. As an example of BiCAT application, in vitro simulation of effective drug combinations used for multiple drug treatment strategies was performed using reagents targeted to BiCAT molecules. The combination treatment based on BiCAT information moderately suppressed cancer cell proliferation compared with single administration, suggesting that the information about BiCAT in cancer cells is useful for the appropriate selection of the combination among molecular targeted reagents. Thus, BiCAT has the potential to contribute to several molecular targeted strategies in future.

A potential novel therapy for FGFR1-amplified pancreatic cancer with bone metastasis, screened by next-generation sequencing and a patient-derived xenograft model

Effective therapies are limited for pancreatic cancer, particularly for those with distant tumour metastases. Therefore, more individualised drug screening is urgently required. Next-generation sequencing (NGS) is a powerful tool to investigate the genomic landscape of patients and the mechanism of drug response, which may provide a broader vision for potential clinical drug screening. Patient-derived xenograft (PDX) models may have a significant advantage in predicting clinical treatment response. In our previous study, a PDX of pancreatic cancer bone metastasis was established, and NGS was conducted to investigate the molecular information. In the present study, these data were further analysed and fibroblast growth factor receptor 1 (FGFR1) amplification was identified in a panel of 416 cancer-associated genes. Thus, AZD4547, an inhibitor against FGFR, was selected as a potential therapy, and was evaluated using the PDX model. AZD4547 was shown to exhibit antitumor activity by reducing the expression of FGFR1 and its targets. The present study also demonstrated the high potential of the novel NGS/PDX-based drug screening platform to improve individualised cancer treatment.

A novel biologic platform elicits profound T cell costimulatory activity and antitumor immunity in mice

Combination immunotherapies utilizing complementary modalities that target distinct tumor attributes or immunosuppressive mechanisms, or engage different arms of the antitumor immune response, can elicit greater therapeutic efficacy than the component monotherapies. Increasing the number of agents included in a therapeutic cocktail can further increase efficacy, however, this approach poses numerous challenges for clinical translation. Here, a novel platform to simplify combination immunotherapy by covalently linking immunotherapeutic agonists to the costimulatory receptors CD134 and CD137 into a single heterodimeric drug, "OrthomAb", is shown. This reagent not only retains costimulatory T cell activity, but also elicits unique T cell functions that are not programmed by either individual agonist, and preferentially expands effector T cells over Tregs. Finally, in an aggressive melanoma model OrthomAb elicits better therapeutic efficacy compared to the unlinked agonists. This demonstration that two drugs can be combined into one provides a framework for distilling complex combination drug cocktails into simpler delivery platforms.

Clinical Equipoise for Trials of Novel Biologic Therapies, Therapeutic Success Rates, and Predictors of Success: A Meta-Analysis

Purpose

The demand for more rapid access to novel biologic therapies than randomized controlled trials can deliver is a topic of ongoing study and debate. We aimed to inform this debate by estimating therapeutic success from phase III trials comparing novel biologic therapies with standard of care and identifying predictors of success.

Methods

This was a meta-analysis of phase III trials evaluating novel biologic therapies in advanced breast, colorectal, lung, and prostate cancers. Therapeutic success was defined as statistically significant results for the primary end point favoring novel biologic therapies.

Results

Of 119 included phase III trials (76,726 patients), therapeutic success was 41%, with a statistically significant relative reduction in disease progression and death for novel biologic therapies over standard of care of 20% and 8%. Therapeutic success did not improve over time (pre-2010, 33%; 2010 to 2014, 44%; P = .2). Predictors of success were a biomarker-selected population (odds ratio, 4.74; 95% CI, 2.05 to 10.95) and progression-free survival end point compared with overall survival (odds ratio, 5.22; 95% CI, 2.41 to 11.39). Phase III trials with a biomarker-selected population showed a larger 28% progression-free survival benefit than phase III trials overall (hazard ratio, 0.72; 95% CI, 0.70 to 0.75) but similar 8% overall survival benefit (hazard ratio, 0.92; 95% CI, 0.90 to 0.94). Therapeutic success of phase III trials with and without a preceding phase II trial were 43% and 30%, respectively

Conclusion

Therapeutic success of novel biologic therapies in phase III trials, including therapies with a matching predictive biomarker, was modest and has not significantly improved over time. Equipoise remains and supports the ongoing ethical and scientific requirement for phase III randomized controlled trials to estimate treatment efficacy and assess the value of potential biomarkers.

Individualized drug screening based on next generation sequencing and patient derived xenograft model for pancreatic cancer with bone metastasis

The efficacy of traditional chemoradiotherapies for pancreatic cancer remains limited, and no effective targeted therapies or screening tests are currently available. Therefore more individualized drug screening is warranted for the clinical treatment of pancreatic cancer. A patient‑derived xenograft (PDX) model of pancreatic cancer bone metastasis was established, and next‑generation sequencing (NGS) was used to investigate the molecular characteristics of the cancer and screen for potential drugs. Immunohistochemical analysis was performed to validate that the PDX retained the molecular characteristics from the patient. Using NGS technology, 13 pancreatic‑cancer‑associated polymorphisms/mutations were identified out of 416 genes sequenced. Based on the sequencing results and associated literatures, AZD6244, a highly selective inhibitor against mitogen‑activated protein kinase kinase 1 (MEK1), was chosen as a potential therapy. AZD6244, a highly selective MEK1 inhibitor, was evaluated as effective for the pancreatic cancer PDX model, and thus may provide potential efficacy in the clinical treatment of the patient with pancreatic cancer investigated in the present study. The feasibility of the novel NGS‑PDX based drug‑screening pattern was demonstrated, and has a potential to improve individua-lized treatment for cancer.

Genetic biomarkers of drug response for small-molecule therapeutics targeting the RTK/Ras/PI3K, p53 or Rb pathway in glioblastoma

Glioblastoma is the most deadly and frequently occurring primary malignant tumor of the central nervous system. Genomic studies have shown that mutated oncogenes and tumor suppressor genes in glioblastoma mainly occur in three pathways: the RTK/Ras/PI3K signaling, the p53 and the Rb pathways. In this review, we summarize the modulatory effects of genetic aberrations in these three pathways to drugs targeting these specific pathways. We also provide an overview of the preclinical efforts made to identify genetic biomarkers of response and resistance. Knowledge of biomarkers will finally promote patient stratification in clinical trials, a prerequisite for trial design in the era of precision medicine.

PET-based molecular imaging in personalized oncology: potential of the assessment of therapeutic outcome

Molecular imaging techniques allow an individualization and optimization of therapy on a patient basis noninvasively. The availability of new hybrid scanners, like PET-computed tomography and PET-MRI allow the combined assessment of changes in morphology and function and are a unique tool for personalized cancer treatment. In particular, it is crucial to identify nonresponders as soon as possible for therapy guidance. The choice of the appropriate therapy and optimal treatment duration can help to avoid side effects and save costs. Furthermore, the development of new specific tracers will enable a more accurate assessment of a therapeutic result. Numerous peptides targeting receptor-active tumors are in development with a high potential in a large spectrum of tumors for theranostic approaches.

Multiparameter Phase I trials: a tool for model-based development of targeted agent combinations--example of EVESOR trial

Optimal development of targeted drug combinations is one of the future challenges to be addressed. Computerization and mathematical models able to describe biological phenomena and to simulate the effects of changes in experimental conditions may help find solutions to this issue. We propose the concept of 'multiparameter trials', where biological, radiological and clinical data required for modeling purpose are collected and illustrated by the ongoing academic EVESOR trial. The objective of the model-based work would be the determination of the optimized doses and dosing schedules of everolimus and sorafenib, offering the maximization of the predicted modeled benefit/toxicity ratio in patients with solid tumors. It may embody the 'proof of concept' of model-based drug development of anticancer agent combinations.

Systemic treatment of advanced hepatocellular carcinoma: from disillusions to new horizons

Hepatocellular carcinoma (HCC) is an aggressive malignancy, which accounts for a third of all cancer deaths globally each year. The management of patients with HCC is complex, as both the tumour stage and any underlying liver disease must be considered conjointly. Since the approval of sorafenib in advanced HCC, several phase III clinical trials have failed to demonstrate any superiority over sorafenib in the frontline setting, and no agent has been shown to impact outcomes after sorafenib failure. This review will focus on the range of experimental therapeutics for patients with advanced HCC and highlight the successes and failures of these treatments as well as areas for future development. Specifics such as dose limiting toxicity and safety profile in patients with liver dysfunction related to the underlying chronic liver disease should be considered when developing therapies in HCC. Finally, robust validated and reproducible surrogate end-points as well as predictive biomarkers should be defined in future randomised trials.

The impact of molecular targets in cancer drug development: major hurdles and future strategies

The last decades were characterized by enormous technological advances resulting in a better understanding of disease pathologies and improvement of treatment strategies. The development of targeted drugs, whose beginning can be traced back to Paul Ehrlich's theory of the 'magic bullet' approximately 100 years ago, is today widely appraised as a promising strategy to combat benign, as well as malignant, diseases. Over 40 years after US President Nixon declared the 'war on cancer', treatment outcome, especially of solid tumors in the advanced stages of disease, still lies far behind expectations. In this perspective article, the authors discuss the recent development of targeted cancer drugs and identify major hurdles. The authors further highlight future strategies that might improve and accelerate the drug-development process.

Mechanistic understanding in clinical practice: complementing evidence-based medicine with personalized medicine

In the last century, medicine has undergone an unprecedented wave of radical changes. From the implementation of surgery up to the development of single gene-targeted therapies, clinical decision making has become increasingly complex to handle. Today, this complexity needs to be rethought in the light of two emerging paradigms: evidence-based medicine (EBM) and personalized medicine (P-Med). The new availability of diverse sources of scientific evidence raises significant issues concerning how clinicians will compare, evaluate and orient their decisions in front of a rapidly growing plethora of therapies, procedures, medical technologies and drugs. In this paper, we compare the background visions behind these two paradigms, evaluating their respective relevance for present and future clinical decision making. In particular, we argue that EBM and P-Med are driven by two diverse modes of reasoning about 'evidence making' in medicine. EBM is grounded on statistical notions and epidemiological data, generally gathered through systematic meta-reviews of randomized controlled trials; P-Med, instead, is grounded on mechanistic explanations of molecular interactions, metabolic pathways and biomarkers. While both paradigms are epistemically sound, we argue that they cannot, and should not, be hybridized into a unique model. Rather, they ought to represent two compatible, but alternative ways of informing the clinical practice. Hence, we conclude that clinicians may expect to see their responsibility increasing as they will deal with diverse, but equally compelling, ways of reasoning and deciding about which intervention will qualify as the 'best one' in each individual case.

Moving molecular targeted drug therapy towards personalized medicine: issues related to clinical trial design

With the event of new Molecular targets, clinical trial design requirements to perform these trials are changing. This paper discusses some of the considerations that need to be taken into account when designing a trial, including those trials that assess combinations of targets.

The challenge to bring personalized cancer medicine from clinical trials into routine clinical practice: the case of the Institut Gustave Roussy

Research with high throughput technologies has propitiated the segmentation of different types of tumors into very small subgroups characterized by the presence of very rare molecular alterations. The identification of these subgroups and the apparition of new agents targeting these infrequent alterations are already affecting the way in which clinical trials are being conducted with an increased need to identify those patients harboring specific molecular alterations. In this review we describe some of the currently ongoing and future studies at the Institut Gustave Roussy that aim for the identification of potential therapeutic targets for cancer patients with the incorporation of high throughput technologies into daily practice including aCGH, next generation sequencing and the creation of a software that allows for target identification specific for each tumor. The initial intention is to enrich clinical trials with cancer patients carrying certain molecular alterations in order to increase the possibility of demonstrating benefit from a targeted agent. Mid and long term aims are to facilitate and speed up the process of drug development as well as to implement the concept of personalized medicine.