An emerging toolkit for targeted cancer therapies

Utility of Precision Oncology Using Cancer Genomic Profiling for Head and Neck Malignancies

BACKGROUND/AIM

In recent years, individual patient cancer genomic profiling (CGP) has become more accessible, allowing determination of therapeutic strategies using driver gene mutations in cancer therapy. However, this precision oncology approach, tailored to specific patients, remains experimental. In this study, we verified the feasibility and benefit of using CGP to guide treatment of malignant head and neck tumors. We aimed to evaluate the profiling and clinical courses of patients with head and neck malignancies who underwent CGP and determine the extent to which CGP for head and neck malignancies has resulted in beneficial drug administration.

PATIENTS AND METHODS

We analyzed CGP results, prognosis, and drug administration status in 27 patients. These patients had completed (or were expected to complete) standard therapy or had rare cancers without standard therapy.

RESULTS

At least one somatic actionable gene alteration was seen in 25 (92.6%) patients, with a median number of actionable alterations per patient of 4 (range=0-11). Drugs in clinical trials were recommended to 22 (81.5%) patients, but none could participate. However, 3 patients (11.1%) could use approved drugs off-label based on CGP results. The most common genetic abnormality was TP53 (66.7%), with TP53 mutations leading to poor prognosis.

CONCLUSION

CGP is clinically useful and serves as a bridge to increase the number of therapeutic options. However, candidate drugs confirmed using CGP may be ineffective when administered. Therefore, oncologists should not blindly accept CGP therapeutic recommendations but should make recommendations that lead to optimal therapies after proper verification.

Current and Emerging Molecular Therapies for Head and Neck Squamous Cell Carcinoma

Head and neck cancer affects nearly 750,000 patients, with more than 300,000 deaths annually. Advances in first line surgical treatment have improved survival rates marginally particularly in developed countries, however survival rates for aggressive locally advanced head and neck cancer are still poor. Recurrent and metastatic disease remains a significant problem for patients and the health system. As our knowledge of the genomic landscape of the head and neck cancers continues to expand, there are promising developments occurring in molecular therapies available for advanced or recalcitrant disease. The concept of precision medicine is underpinned by our ability to accurately sequence tumour samples to best understand individual patient genomic variations and to tailor targeted therapy for them based on such molecular profiling. Not only is their purported response to therapy a factor of their genomic variation, but so is their inclusion in biomarker-driven personalised medicine therapeutic trials. With the ever-expanding number of molecular druggable targets explored through advances in next generation sequencing, the number of clinical trials assessing these targets has significantly increased over recent years. Although some trials are focussed on first-line therapeutic approaches, a greater majority are focussed on locally advanced, recurrent or metastatic disease. Similarly, although single agent monotherapy has been found effective in some cases, it is the combination of drugs targeting different signalling pathways that seem to be more beneficial to patients. This paper outlines current and emerging molecular therapies for head and neck cancer, and updates readers on outcomes of the most pertinent clinical trials in this area while also summarising ongoing efforts to bring more molecular therapies into clinical practice.

Molecular Pathways and Druggable Targets in Head and Neck Squamous Cell Carcinoma

Head and neck cancers are a heterogeneous group of neoplasms, affecting an ever increasing global population. Despite advances in diagnostic technology and surgical approaches to manage these conditions, survival rates have only marginally improved and this has occurred mainly in developed countries. Some improvements in survival, however, have been a result of new management and treatment approaches made possible because of our ever-increasing understanding of the molecular pathways triggered in head and neck oncogenesis, and the growing understanding of the abundant heterogeneity of this group of cancers. Some important pathways are common to other solid tumours, but their impact on reducing the burden of head and neck disease has been less than impressive. Other less known and little-explored pathways may hold the key to the development of potential druggable targets. The extensive work carried out over the last decade, mostly utilising next generation sequencing has opened up the development of many novel approaches to head and neck cancer treatment. This paper explores our current understanding of the molecular pathways of this group of tumours and outlines associated druggable targets which are deployed as therapeutic approaches in head and neck oncology with the ultimate aim of improving patient outcomes and controlling the personal and economic burden of head and neck cancer.

Amplicon-Based NGS Panels for Actionable Cancer Target Identification in Follicular Cell-Derived Thyroid Neoplasia

Follicular cell-derived thyroid cancers are heterogenous and morphological classification is a complex and highly specialized task. Hence, identification of somatic alterations could provide insights to tumor biology and serve as an add-on diagnostic tool. Furthermore, results from these add-on tools could point in the direction of a more personalized treatment strategy. In the present study we set out to identify and validate the somatic mutation profile in a sample-set of follicular cell-derived thyroid neoplasia. One-hundred-and-one archived formalin fixed paraffin embedded (FFPE) tissue samples from patients diagnosed with follicular cell-derived thyroid neoplasia were included, and upon DNA-extraction and qualitative measurements 99 samples were eligible for amplicon-based next-generation-sequencing. Libraries were generated using the TruSeq Amplicon Cancer Panel, followed by sequencing using a MiSeq. Upon data processing and variant filtering all variants were manually assessed to exclude false positive mutations in the final curated list. Moreover, hot-spot mutations were validated using an independent platform from Agilent. Each diagnostic group were correlated to mutation burden and individual mutations were classified according to recent guidelines for somatic mutation classification. Close to 100% of the archived FFPE samples were eligible for DNA-library preparation and amplicon sequencing based on DNA quality criterion. The distribution of mutations in the specific diagnostic groups resulted in a higher mutation frequency among the most dedifferentiated than in the groups with a more differentiated cell profile. Based on the distribution mutations across the samples and using hierarchical clustering, we generated four tentative mutational signatures; highly mutated tumors; tumors with mainly NRAS and TP53 mutations; BRAF mutated tumors and tumors with none or single sporadic mutations. Future studies including more samples and follow-up data may amend these signatures, however our results imply that morphological classification of follicular cell derived thyroid neoplasia could be supplemented with a somatic mutational signature. Taken together, broad screening of the somatic alterations in FFPE tissue of thyroid neoplasia is comprehensible and essential for future identification of possible treatment targets and personalized medicine.

The many faces of mathematical modelling in oncology

The application of modelling to solve problems in biology and medicine, and specifically in oncology and radiation therapy, is increasingly established and holds big promise. We provide an overview of the basic concepts of the field and its current state, along with new tools available and future directions for research. We will outline radiobiology models, examples of other anticancer therapy models, multiscale modelling, and we will discuss mechanistic and phenomenological approaches to modelling.

Targeting therapeutic liabilities engendered by PIK3R1 mutations for cancer treatment

The regulatory subunit of PI3K, p85α (encoded by PIK3R1), binds, stabilizes and inhibits the PI3K p110 catalytic subunit. Functional characterization of PIK3R1 mutations has identified not only hypomorphs with reduced inhibition of p110, but also hypomorphs and dominant negative mutants that disrupt a novel regulatory role of p85α on PTEN or neomorphs that activate unexpected signaling pathways. The diverse phenotypic spectrum of these PIK3R1 driver mutations underscores the need for different treatment strategies targeting tumors harboring these mutations. This article describes the functional consequences of the spectrum of PIK3R1 driver mutations and therapeutic liabilities they may engender.

Leaving the lysosome behind: novel developments in autophagy inhibition

The search for a single silver bullet for the treatment of cancer has now been overshadowed by the identification of multiple therapeutic targets unique to each malignancy and even to each patient. In recent years, autophagy has emerged as one such therapeutic target. In response to both therapeutic and oncogenic stress, cancer cells upregulate and demonstrate an increased dependence upon this intracellular recycling process. Particularly in malignancies that currently lack targeted therapeutic options, autophagy inhibitors are the next hopeful prospects for the treatment of this disease. In this review, we discuss the rapid evolution of autophagy inhibitors from early lysosomotropic agents to next-generation lysosome-targeted drugs and beyond.

Cancer beyond organ and tissue specificity: next-generation-sequencing gene mutation data reveal complex genetic similarities across major cancers

Cancer medicine relies on the paradigm that cancer is an organ- and tissue-specific disease, which is the basis for classifying tumors. With the extensive genomic information now available on tumors it is possible to conduct analyses to reveal common genetic features across cancer types and to explore whether the established anatomy-based tumor classification is actually reflected on the genetic level, which might provide important guides to new therapeutic directions. Here, we have conducted an extensive analysis of the genetic similarity of tumors from 14 major cancer entities using somatic mutation data from 4,796 cases available through The Cancer Genome Atlas (TCGA) based on all available genes as well as different cancer-related gene sets. Our analysis provides a systematic account of the genetic similarity network for major cancer types and shows that in about 43% of the cases on average, tumors of a particular anatomic site are genetically more similar to tumors from different organs and tissues (trans-similarity) than to tumors of the same origin (self-similarity). The observed similarities exist not only for carcinomas from different sites but are also present among neoplasms from different tissue origin, such as melanoma, acute myeloid leukemia, and glioblastoma. The current WHO cancer classification is therefore reflected on the genetic level by only about 57% of the tumors. These results provide a rationale to reconsider organ- and tissue-specificity in cancer and contribute to the discussion about whether personalized therapies targeting specific genetic alterations may be transferred to cancers from other anatomic sites with similar genetic properties.

Cancer Systems Biology: a peek into the future of patient care?

Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function, or the effect that mutating one protein has on a biological phenotype. A range of technologies is beginning to provide information that will enable a holistic view of how genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, and at the organ and organism level. This process, termed Systems Biology, needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients who are most likely to benefit from targeted therapies and for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current-often short term-effects of targeted therapies into durable responses, ultimately to improve patient quality of life and provide a cure.

Genomic Medicine Frontier in Human Solid Tumors: Prospects and Challenges

Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the “one test-one drug” paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.

Advancing personalized cancer medicine in lung cancer

Although improvements in genomic technologies during the past decade have greatly advanced our understanding of the genomic alterations that contribute to lung cancer, and the disease has (to a degree) become a paradigm for individualized cancer treatment in solid tumors, additional challenges must be addressed before the goal of personalized cancer therapy can become a reality for lung cancer patients.

Biospecimens, biomarkers, and burgeoning data: the imperative for more rigorous research standards

Knowledge of the altered molecular landscapes in disease offers great promise for developing biomarker-based tests to improve diagnosis and optimize treatment. Progress in biomarker research has been frustratingly slow due to the poor clinical trial design and the lack of standards for specimen collection, biomarker analysis, and data reporting. The ability of high throughput genomics, proteomics, and other 'omics' platforms to profile a large number of analytes in a single assay, together with the pending prospect of rapid expansion of whole exome and whole genome sequencing for clinical use, is increasing the technical and logistical complexity of biomarker validation. Harnessing these new technologies and improved productivity in biomarker validation will depend on adopting systems-based approaches and require major changes in the organization and funding strategies for biomarker research. A systems approach will require new multi-institution collaborations, the integration of diverse technical and clinical activities, greater engagement of industry, and education of regulators, clinicians, and payers about how to use biomarkers for improved patient management and clinical outcomes.

Overcoming implementation challenges of personalized cancer therapy

Personalized cancer therapy is based on the precept that detailed molecular characterization of the patient's tumour and its microenvironment will enable tailored therapies to improve outcomes and decrease toxicity. The goal of personalized therapy is to target aberrations that drive tumour growth and survival, by administering the right drug combination for the right person. This is becoming increasingly achievable with advances in high-throughput technologies to characterize tumours and the expanding repertoire of molecularly targeted therapies. However, there are numerous challenges that need to be surpassed before delivering on the promise of personalized cancer therapy. These include tumour heterogeneity and molecular evolution, costs and potential morbidity of biopsies, lack of effective drugs against most genomic aberrations, technical limitations of molecular tests, and reimbursement and regulatory hurdles. Critically, the 'hype' surrounding personalized cancer therapy must be tempered with realistic expectations, which, today, encompass increased survival times for only a portion of patients.