This brief perspective article focuses on the most common errors and pitfalls, as well as the do's and don'ts in drug combination studies, in terms of experimental design, data acquisition, data interpretation, and computerized simulation. The Chou-Talalay method for drug combination is based on the median-effect equation, derived from the mass-action law principle, which is the unified theory that provides the common link between single entity and multiple entities, and first order and higher order dynamics. This general equation encompasses the Michaelis-Menten, Hill, Henderson-Hasselbalch, and Scatchard equations in biochemistry and biophysics. The resulting combination index (CI) theorem of Chou-Talalay offers quantitative definition for additive effect (CI = 1), synergism (CI 1) in drug combinations. This theory also provides algorithms for automated computer simulation for synergism and/or antagonism at any effect and dose level, as shown in the CI plot and isobologram, respectively.

https://cancerres.aacrjournals.org/content/canres/70/2/440.full.pdf

Drug Combination Studies and Their Synergy Quantification Using the Chou-Talalay Method

The median-effect equation derived from the mass-action law principle at equilibrium-steady state via mathematical induction and deduction for different reaction sequences and mechanisms and different types of inhibition has been shown to be the unified theory for the Michaelis-Menten equation, Hill equation, Henderson-Hasselbalch equation, and Scatchard equation. It is shown that dose and effect are interchangeable via defined parameters. This general equation for the single drug effect has been extended to the multiple drug effect equation for n drugs. These equations provide the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI 1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to allow automated simulation of synergism and antagonism at all dose or effect levels. It displays the dose-effect curve, median-effect plot, combination index plot, isobologram, dose-reduction index plot, and polygonogram for in vitro or in vivo studies. This theoretical development, experimental design, and computerized data analysis have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical sciences. In this review, selected examples of applications are given, and step-by-step examples of experimental designs and real data analysis are also illustrated. The merging of the mass-action law principle with mathematical induction-deduction has been proven to be a unique and effective scientific method for general theory development. The median-effect principle and its mass-action law based computer software are gaining increased applications in biomedical sciences, from how to effectively evaluate a single compound or entity to how to beneficially use multiple drugs or modalities in combination therapies.

http://www.protocol-online.org/forums/uploads/monthly_09_2010/post-8165-008503000%201284677034.ipb

Theoretical Basis, Experimental Design, and Computerized Simulation of Synergism and Antagonism in Drug Combination Studies

Cisplatin is one of the most potent antitumor agents known, displaying clinical activity against a wide variety of solid tumors. Its cytotoxic mode of action is mediated by its interaction with DNA to form DNA adducts, primarily intrastrand crosslink adducts, which activate several signal transduction pathways, including those involving ATR, p53, p73, and MAPK, and culminate in the activation of apoptosis. DNA damage-mediated apoptotic signals, however, can be attenuated, and the resistance that ensues is a major limitation of cisplatin-based chemotherapy. The mechanisms responsible for cisplatin resistance are several, and contribute to the multifactorial nature of the problem. Resistance mechanisms that limit the extent of DNA damage include reduced drug uptake, increased drug inactivation, and increased DNA adduct repair. Origins of these pharmacologic-based mechanisms, however, are at the molecular level. Mechanisms that inhibit propagation of the DNA damage signal to the apoptotic machinery include loss of damage recognition, overexpression of HER-2/neu, activation of the PI3-K/Akt (also known as PI3-K/PKB) pathway, loss of p53 function, overexpression of antiapoptotic bcl-2, and interference in caspase activation. The molecular signature defining the resistant phenotype varies between tumors, and the number of resistance mechanisms activated in response to selection pressures dictates the overall extent of cisplatin resistance.

/pdf/cisplatin-mode-of-cytotoxic-action-and-molecular-basis-of-57e8cf7is5.pdf

Cisplatin: mode of cytotoxic action and molecular basis of resistance

Pathology and genetics of tumours of the urinary system and male genital organs

Platinum-based drugs, and in particular cis-diamminedichloroplatinum(II) (best known as cisplatin), are employed for the treatment of a wide array of solid malignancies, including testicular, ovarian, head and neck, colorectal, bladder and lung cancers. Cisplatin exerts anticancer effects via multiple mechanisms, yet its most prominent (and best understood) mode of action involves the generation of DNA lesions followed by the activation of the DNA damage response and the induction of mitochondrial apoptosis. Despite a consistent rate of initial responses, cisplatin treatment often results in the development of chemoresistance, leading to therapeutic failure. An intense research has been conducted during the past 30 years and several mechanisms that account for the cisplatin-resistant phenotype of tumor cells have been described. Here, we provide a systematic discussion of these mechanism by classifying them in alterations (1) that involve steps preceding the binding of cisplatin to DNA (pre-target resistance), (2) that directly relate to DNA-cisplatin adducts (on-target resistance), (3) concerning the lethal signaling pathway(s) elicited by cisplatin-mediated DNA damage (post-target resistance) and (4) affecting molecular circuitries that do not present obvious links with cisplatin-elicited signals (off-target resistance). As in some clinical settings cisplatin constitutes the major therapeutic option, the development of chemosensitization strategies constitute a goal with important clinical implications.

Molecular mechanisms of cisplatin resistance

Publisher Summary The chapter analyzes the origin of nongerm cell tumor elements within germ cell tumors and midline tumors of uncertain histogenesis. The chapter presents a summary of findings demonstrating the use of conventional and molecular cytogenetic methods to detect i(12p) in tumors of uncertain histogenesis and in nongerminal cell types found coexisting with GCT. Twenty-eight fresh tumor specimens were obtained from 28 patients referred for management of midline tumors of uncertain origin, where previous biopsies had failed to establish a specific diagnosis. Specimens were evaluated by routine histopathology, immunohistochemistry, and electron microscopy, and conventional and/or molecular cytogenetic methods. In addition, using cytogenetic techniques, four neoplasms that had developed in patients with known GCTs were analyzed. Two cases involved acute nonlymphoblastic leukemia (ANLL); one case involved an embryonal rhabdomyosarcoma with a coexistent primary mediastinal NSGCT and one case presented with a small cell neuroendocrine carcinoma and a testicular NSGCT. Seven patients with i(12p)-positive tumors were treated with cisplatin-based therapy; this resulted in five complete (CR) and one partial response (PR) and three long-term survivors. In contrast, in 17 patients without a GCT-related cytogenetic marker, CDDP-based chemotherapy resulted in only two PR (p=.009) and no long-term survivors.

The Origin of Non-Germ Cell Tumour Elements within Germ Cell Tumours and Midline Tumours of Uncertain Histogenesis

720: Primary Retroperitoneal Lymph Node Dissection (P-RPLND) Versus Induction Chemotherapy (IC) for the Management of Clinical Stage (CS) IIA and IIB Nonseminomatous Germ Cell Testicular Cancer (NSGCT)

Publisher Summary This chapter discusses the developments in management of germ cell tumors. Germ cell tumors are recognized as one of the most curable of all tumors. Approximately 90% of newly diagnosed patients can be cured. The identification and application of new chemotherapy programs have impacted the management of patients with all stages and histologies by providing the possibility of cure to those with metastatic disease and options for less aggressive intervention, including observation, for those with lower stage disease. Clinical trials for poor-risk disease have been less rewarding. Cisplatin doses of 200 mg/m2 per cycle are not superior to standard doses of 100–120 mg/m2 per cycle in conjunction with other agents. A wide range of treatment response projections and survival outcomes was reported over many poor-risk trials. The differences in allocation criteria for poor-risk status proved to be critical in these clinical trials. Identification of active drugs in the salvage setting and the efficacy of high-dose chemotherapy with stem-cell support led to clinical trials attempting to incorporate them into primary treatment. The chapter presents the results of three clinical trials of more intensive therapy as first therapy in poor-risk patients.

Germ Cell Tumours: Past, Present and Future

https://acsjournals.onlinelibrary.wiley.com/doi/pdf/10.3322/canjclin.33.3.139

Adjuvant chemotherapy in the management of stage III and IV tumors of the head and neck.

Four methods for assigning patients with germ cell tumours to poor risk programmes were compared using 118 consecutive patients treated on ‘good’ and ‘poor’ risk studies. The median survival of patients deemed poor risk by Memorial Sloan-Kettering Cancer Center was 11 months, by Indiana University 15 months, by the National Cancer Institute 15 months, and by the European Organization for Research on the Treatment of Cancer 23.5 months. The major differences between these criteria were in the use of pretreatment tumour marker values, and the use of specific sites of metastases as independent prognostic variables. These data imply that a variable number of good prognosis patients enter some poor risk trials, the number being dependent upon the criteria used. Poor risk criteria should be as restrictive as possible in order to avoid over treating good risk patients, and to avoid artificially inflated response rates resulting from the successful treatment of such poor risk patients.

An analysis of poor risk assignment in patients with germ cell tumours.

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