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AACR-FDA-NCI Cancer Biomarkers Collaborative Consensus Report: Advancing the Use of Biomarkers in Cancer Drug Development

Recent discoveries in cancer biology have greatly increased our understanding of cancer at the molecular and cellular level, but translating this knowledge into safe and effective therapies for cancer patients has proved to be challenging. There is a growing imperative to modernize the drug development process by incorporating new techniques that can predict the safety and effectiveness of new drugs faster, with more certainty, and at lower cost. Biomarkers are central to accelerating the identification and adoption of new therapies, but currently, many barriers impede their use in drug development and clinical practice. In 2007, the AACR-FDA-NCI Cancer Biomarkers Collaborative stepped into the national effort to bring together disparate stakeholders to clearly delineate these barriers, to develop recommendations for integrating biomarkers into the cancer drug development enterprise, and to set in motion the necessary action plans and collaborations to see the promise of biomarkers come to fruition, efficiently delivering quality cancer care to patients.

https://aacrjournals.org/clincancerres/article/16/13/3299/11147/AACR-FDA-NCI-Cancer-Biomarkers-Collaborative

Mini-review. Application of combinatorial library methods in cancer research and drug discovery

Combinatorial chemistry is now considered as one of the most important recent advances in medicinal chemistry. There are five general approaches in combinatorial peptide library methods: biological libraries; spatially addressable parallel solid phase or solution phase libraries; synthetic library methods requiring deconvolution; the 'one-bead one-compound' library method; and synthetic library methods using affinity chromatography selection. Except for the biological library approach, which is limited to peptide libraries with eukaryotic amino acids, all the other four synthetic approaches are applicable to peptide, non-peptide oligomer or small molecule libraries. Although non-peptide, or small molecule libraries are generally prepared by a synthetic approach, recent advances in biosynthetic methods using enzymes may enable one to prepare chemical libraries that are otherwise difficult to synthesize chemically. In the 'one-bead one-compound' library method every member of the library is screened in parallel, but the chemical structure of the positive compound-bead has to be determined either directly or via an encoding strategy. A reliable high-throughput biological assay is needed for a successful combinatorial library screen. Solid-phase binding or functional assays as well as solution phase assays have been used successfully in various library methods. There has been enormous progress in the technological advances or molecular biology and the fundamental understanding of the molecular basis of cancer in recent years. By applying combinatorial chemistry and computational chemistry to the many cancer targets that have recently been identified, it is hopeful that more potent, more specific and less toxic anti-cancer agents will be developed in the foreseeable future. In addition to being a great tool for drug discovery, combinatorial chemistry has also proven to be invaluable in basic research. A few specific examples of the applications of combinatorial chemistry in basic cancer research and drug discovery are described in this min-review.

https://www.ingentaconnect.com/content/cog/antcan/1997/00000012/00000003/art00001

Translating cancer research into targeted therapeutics

The emphasis in cancer drug development has shifted from cytotoxic, non-specific chemotherapies to molecularly targeted, rationally designed drugs promising greater efficacy and less side effects. Nevertheless, despite some successes drug development remains painfully slow. Here, we highlight the issues involved and suggest ways in which this process can be improved and expedited. We envision an increasing shift to integrated cancer research and biomarker-driven adaptive and hypothesis testing clinical trials. The goal is the development of specific cancer medicines to treat the individual patient, with treatment selection being driven by a detailed understanding of the genetics and biology of the patient and their cancer.

https://www.nature.com/articles/nature09339

Guidelines for the welfare and use of animals in cancer research

Animal experiments remain essential to understand the fundamental mechanisms underpinning malignancy and to discover improved methods to prevent, diagnose and treat cancer. Excellent standards of animal care are fully consistent with the conduct of high quality cancer research. Here we provide updated guidelines on the welfare and use of animals in cancer research. All experiments should incorporate the 3Rs: replacement, reduction and refinement. Focusing on animal welfare, we present recommendations on all aspects of cancer research, including: study design, statistics and pilot studies; choice of tumour models (e.g., genetically engineered, orthotopic and metastatic); therapy (including drugs and radiation); imaging (covering techniques, anaesthesia and restraint); humane endpoints (including tumour burden and site); and publication of best practice.

https://www.nature.com/articles/6605642

Hiding in plain view: the potential for commonly used drugs to reduce breast cancer mortality

Many medications have been developed for one purpose but then are found to have other clinical activities. There is tremendous interest in whether non-cancer medications may potentially have effects on breast cancer survival. In this review article, we have presented and evaluated the evidence for several commonly used over-the-counter and prescription medications - including aspirin (and other non-steroidal anti-inflammatory drugs), beta-blockers, angiotensin-converting enzyme inhibitors, statins, digoxin, and metformin - that have been evaluated among breast cancer survivors in prospective studies. Substantial scientific evidence supports the hypothesis that some of these common and relatively safe drugs may reduce breast cancer mortality among those with the disease by an amount that rivals the mortality reduction gained by currently used therapies. In particular, the evidence is strongest for aspirin (approximately 50% reduction), statins (approximately 25% reduction), and metformin (approximately 50% reduction). As these drugs are generic and inexpensive, there is little incentive for the pharmaceutical industry to fund the randomized trials that would show their effectiveness definitively. We advocate that confirmation of these findings in randomized trials be considered a high research priority, as the potential impact on human lives saved could be immense.

https://link.springer.com/article/10.1186/bcr3336

Computational models for predicting drug responses in cancer research 

The computational prediction of drug responses based on the analysis of multiple types of genome-wide molecular data is vital for accomplishing the promise of precision medicine in oncology. This will benefit cancer patients by matching their tumor characteristics to the most effective therapy available. As larger and more diverse layers of patient-related data become available, further demands for new bioinformatics approaches and expertise will arise. This article reviews key strategies, resources and techniques for the prediction of drug sensitivity in cell lines and patient-derived samples. It discusses major advances and challenges associated with the different model development steps. This review highlights major trends in this area, and will assist researchers in the assessment of recent progress and in the selection of approaches to emerging applications in oncology.

https://academic.oup.com/bib/article/18/5/820/2562791

Organoids in cancer research

The recent advances in in vitro 3D culture technologies, such as organoids, have opened new avenues for the development of novel, more physiological human cancer models. Such preclinical models are essential for more efficient translation of basic cancer research into novel treatment regimens for patients with cancer. Wild-type organoids can be grown from embryonic and adult stem cells and display self-organizing capacities, phenocopying essential aspects of the organs they are derived from. Genetic modification of organoids allows disease modelling in a setting that approaches the physiological environment. Additionally, organoids can be grown with high efficiency from patient-derived healthy and tumour tissues, potentially enabling patient-specific drug testing and the development of individualized treatment regimens. In this Review, we evaluate tumour organoid protocols and how they can be utilized as an alternative model for cancer research.

https://www.nature.com/articles/s41568-018-0007-6

Long-term Use of Cholesterol-Lowering Drugs and Cancer Incidence in a Large United States Cohort 

HMG-coA reductase inhibitors, commonly known as statins, account for the great majority of cholesterol-lowering drug use. However, little is known about the association between long-term statin use and incidence of most types of cancers. We examined the association between long-term use of cholesterol-lowering drugs, predominantly statins, and the incidence of ten common cancers, as well as overall cancer incidence, among 133,255 participants (60,059 men and 73,196 women) in the Cancer Prevention Study II Nutrition Cohort during the period from 1997 to 2007. Multivariate Cox proportional hazards regression was used to estimate relative risks (RR). Current use status and duration of use were updated during follow-up using information from biennial follow-up questionnaires. Current use of cholesterol-lowering drugs for five or more years was not associated with overall cancer incidence (RR = 0.97, 95% CI = 0.92–1.03), or incidence of prostate, breast, colorectal, lung, bladder, renal cell, or pancreatic cancer but was associated with lower risk of melanoma (RR = 0.79, 95% CI = 0.66–0.96), endometrial cancer (RR = 0.65, 95% CI = 0.45–0.94), and non-Hodgkin lymphoma (NHL; RR = 0.74, 95% CI = 0.62–0.89). These results suggest that long-term use of statins is unlikely to substantially increase or decrease overall cancer risk. However, associations between long-term statin use and risk of endometrial cancer, melanoma, and NHL deserve further investigation. 

https://aacrjournals.org/cancerres/article/71/5/1763/569918/Long-term-Use-of-Cholesterol-Lowering-Drugs-and

Patient-Derived Xenograft Models: An Emerging Platform for Translational Cancer Research

Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models.

https://aacrjournals.org/cancerdiscovery/article/4/9/998/6397/Patient-Derived-Xenograft-Models-An-Emerging

Therapeutic Nanoparticles for Drug Delivery in Cancer 

Cancer nanotherapeutics are rapidly progressing and are being implemented to solve several limitations of conventional drug delivery systems such as nonspecific biodistribution and targeting, lack of water solubility, poor oral bioavailability, and low therapeutic indices. To improve the biodistribution of cancer drugs, nanoparticles have been designed for optimal size and surface characteristics to increase their circulation time in the bloodstream. They are also able to carry their loaded active drugs to cancer cells by selectively using the unique pathophysiology of tumors, such as their enhanced permeability and retention effect and the tumor microenvironment. In addition to this passive targeting mechanism, active targeting strategies using ligands or antibodies directed against selected tumor targets amplify the specificity of these therapeutic nanoparticles. Drug resistance, another obstacle that impedes the efficacy of both molecularly targeted and conventional chemotherapeutic agents, might also be overcome, or at least reduced, using nanoparticles. Nanoparticles have the ability to accumulate in cells without being recognized by P-glycoprotein, one of the main mediators of multidrug resistance, resulting in the increased intracellular concentration of drugs. Multifunctional and multiplex nanoparticles are now being actively investigated and are on the horizon as the next generation of nanoparticles, facilitating personalized and tailored cancer treatment.

https://aacrjournals.org/clincancerres/article/14/5/1310/179797/Therapeutic-Nanoparticles-for-Drug-Delivery-in

Cancer Cell Lines for Drug Discovery and Development 

Despite the millions of dollars spent on target validation and drug optimization in preclinical models, most therapies still fail in phase III clinical trials. Our current model systems, or the way we interpret data from them, clearly do not have sufficient clinical predictive power. Current opinion suggests that this is because the cell lines and xenografts that are commonly used are inadequate models that do not effectively mimic and predict human responses. This has become such a widespread belief that it approaches dogma in the field of drug discovery and optimization and has spurred a surge in studies devoted to the development of more sophisticated animal models such as orthotopic patient-derived xenografts in an attempt to obtain more accurate estimates of whether particular cancers will respond to given treatments. Here, we explore the evidence that has led to the move away from the use of in vitro cell lines and toward various forms of xenograft models for drug screening and development. We review some of the pros and cons of each model and give an overview of ways in which the use of cell lines could be modified to improve the predictive capacity of this well-defined model. 

https://aacrjournals.org/cancerres/article/74/9/2377/599415/Cancer-Cell-Lines-for-Drug-Discovery-and

Novel Chemotherapeutic Drugs in Sphingolipid Cancer Research

Sphingolipid-metabolizing enzymes are becoming targets for chemotherapeutic development with an increasing interest in the recent years. In this chapter we introduce the sphingolipid family of lipids, and the role of individual species in cell homeostasis. We also discuss their roles in several rare diseases and overall, in cancer transformation. We follow the biosynthesis pathway of the sphingolipid tree, focusing on the enzymes in order to understand how using small molecule inhibitors makes it possible to modulate cancer progression. Finally, we describe the most used and historically significant inhibitors employed in cancer research, their relationships to sphingolipid metabolism, and some promising results found in this field.

https://link.springer.com/chapter/10.1007/978-3-7091-1368-4_12

Breast Cancer and Nonsteroidal Anti-Inflammatory Drugs

We analyzed data from the prospective Women’s Health Initiative (WHI) Observational Study to examine the effects of regular use of aspirin, ibuprofen, and other nonsteroidal anti-inflammatory drugs (NSAIDs) on breast cancer risk. We studied a population of 80,741 postmenopausal women between 50 and 79 years of age who reported no history of breast cancer or other cancers (excluding nonmelanoma skin cancer), and we completed a personal baseline interview that elicited comprehensive health information including data on breast cancer risk factors and NSAID use. All of the cases were adjudicated by WHI physicians using pathology reports. Our analysis was based on 1392 confirmed cases of breast cancer. Relative risks (RRs) with 95% confidence intervals (CIs) were estimated with adjustment for age and other breast cancer risk factors. Regular NSAID use (two or more tablets/week) for 5–9 years produced a 21% reduction in the incidence of breast cancer (RR, 0.79; 95% CI, 0.60–1.04); regular NSAID use for 10 or more years produced a 28% reduction (RR, 0.72; CI, 0.56–0.91), and there was a statistically significant inverse linear trend of breast cancer incidence with the duration of NSAID use (P < 0.01). The estimated risk reduction for long-term use of ibuprofen (RR, 0.51; CI, 0.28–0.96) was greater than for aspirin (RR, 0.79; CI, 0.60–1.03). Subgroup analysis by breast cancer risk factors did not result in effect modification. Regular use of acetaminophen (an analgesic agent with little or no anti-inflammatory activity) or low-dose aspirin (<100 mg) was unrelated to the incidence of breast cancer. Our results indicate that the regular use of aspirin, ibuprofen, or other NSAIDs may have a significant chemopreventive effect against the development of breast cancer and underscore the need for clinical trials to confirm this effect.

https://aacrjournals.org/cancerres/article/63/18/6096/510377/Breast-Cancer-and-Nonsteroidal-Anti-Inflammatory

From microRNA functions to microRNA therapeutics: Novel targets and novel drugs in breast cancer research and treatment

MicroRNAs (miRNAs or miRs) are a family of small non‑coding RNAs that regulate gene expression by the sequence-selective targeting of mRNAs, leading to translational repression or mRNA degradation, depending on the degree of complementarity with target mRNA sequences. miRNAs play a crucial role in cancer. In the case of breast tumors, several studies have demonstrated a correlation between: i) the expression profile of oncogenic miRNAs (oncomiRs) and tumor suppressor miRNAs; and ii) the tumorigenic potential of triple-negative [estrogen receptor (ER), progesterone receptor (PR) and Her2/neu] primary breast cancers. Among the miRNAs involved in breast cancer, miR-221 plays a crucial role for the following reasons: i) miR-221 is significantly overexpressed in triple-negative primary breast cancer; ii) the oncosuppressor p27Kip1, a validated miR-221 target is downregulated in aggressive cancer cell lines; and iii) the upregulation of a key transcription factor, Slug, appears to be crucial, since it binds to the miR-221/miR-222 promoter and is responsible for the high expression of the miR-221/miR-222 cluster in breast cancer cells. A Slug/miR-221 network has been suggested, linking miR-221 activity with the downregulation of a Slug repressor, leading to Slug/miR-221 upregulation and p27Kip1 downregulation. Interference with this process can be achieved using antisense miRNA (antagomiR) molecules targeting miR-221, inducing the downregulation of Slug and the upregulation of p27Kip1.

https://www.spandidos-publications.com/10.3892/ijo.2013.2059

A History of Cancer Chemotherapy

The use of chemotherapy to treat cancer began at the start of the 20th century with attempts to narrow the universe of chemicals that might affect the disease by developing methods to screen chemicals using transplantable tumors in rodents. It was, however, four World War II–related programs, and the effects of drugs that evolved from them, that provided the impetus to establish in 1955 the national drug development effort known as the Cancer Chemotherapy National Service Center. The ability of combination chemotherapy to cure acute childhood leukemia and advanced Hodgkin's disease in the 1960s and early 1970s overcame the prevailing pessimism about the ability of drugs to cure advanced cancers, facilitated the study of adjuvant chemotherapy, and helped foster the national cancer program. Today, chemotherapy has changed as important molecular abnormalities are being used to screen for potential new drugs as well as for targeted treatments.

https://aacrjournals.org/cancerres/article/68/21/8643/541799/A-History-of-Cancer-Chemotherapy