Toward the individualization of lung cancer therapy

Polyethylene glycol-modified nanoscale conjugated polymer for the photothermal therapy of lung cancer

Killing tumor cells efficiently with photothermal therapy remains a huge challenge. In this study, we successfully prepared a novel polymer with photothermal conversion capability via a condensation reaction, and then subjected it to Polyethylene glycol (PEG) modification and ultrasonic nanocrystalline treatment to make it suitable forin vivophotothermal therapy applications. The conjugated polymer demonstrated good biocompatibility and photothermal conversion ability and was shown in cell experiments to be effective in killing tumor cells after laser irradiation. In addition, the conjugated polymer-based photothermal therapy, guided by photoacoustic real-time imaging and mediated by laser irradiation, of a tumor-bearing mouse model could effectively inhibit the growth of tumor tissue and demonstrated goodin vivobiosafety. Thus, photothermal therapy based on the conjugated polymer synthesized in this study provides a new idea and strategy for the treatment of lung cancer.

SMARCA4-inactivating mutations increase sensitivity to Aurora kinase A inhibitor VX-680 in non-small cell lung cancers

Mutations in the SMARCA4/BRG1 gene resulting in complete loss of its protein (BRG1) occur frequently in non-small cell lung cancer (NSCLC) cells. Currently, no single therapeutic agent has been identified as synthetically lethal with SMARCA4/BRG1 loss. We identify AURKA activity as essential in NSCLC cells lacking SMARCA4/BRG1. In these cells, RNAi-mediated depletion or chemical inhibition of AURKA induces apoptosis and cell death in vitro and in xenograft mouse models. Disc large homologue-associated protein 5 (HURP/DLGAP5), required for AURKA-dependent, centrosome-independent mitotic spindle assembly is essential for the survival and proliferation of SMARCA4/BRG1 mutant but not of SMARCA4/BRG1 wild-type cells. AURKA inhibitors may provide a therapeutic strategy for biomarker-driven clinical studies to treat the NSCLCs harbouring SMARCA4/BRG1-inactivating mutations.

Lung cancers often harbour loss-of-function mutations in SMARCA4. Here, the authors demonstrate a vulnerability of SMARCA4-deficient lung cancers for Aurora kinase A inhibition associated with mitotic defects.

A patient-derived xenograft mouse model generated from primary cultured cells recapitulates patient tumors phenotypically and genetically

BACKGROUND

Preclinical trials of cancer therapeutics require both in vitro and in vivo evaluations. Recently, a patient-derived xenograft model in immunodeficient mice has been reported as a valuable in vivo evaluation system. In our current study, we aimed to establish a more efficient and accurate system for preclinical trials by generating primary cancer cells from patients and performing xenograft transfers of these cells into mice.

METHODS

Human lung cancer specimens (n = 4) obtained from chemo-naive patients were cultured in bronchiolar epithelial basal medium supplemented with growth factors, followed by inoculation into non-obese diabetic/severe combined immunodeficient mice. The generated tumors in the mice were validated phenotypically and genetically using the original specimen and primary cancer cells.

RESULTS

Immunohistochemical analysis of marker proteins, including cytokeratin 7, cytokeratin 20, epidermal growth factor receptor, thyroid transcription factor-1, CD56, chromogranin, and synaptophysin, demonstrated that the xenograft tumors were originated from the patient tumors. Moreover, mutation profiling using the OncoMap System, which analyzes mutations at 440 sites in 41 tumor-related genes, showed the same patterns in both the patient and xenograft tumors.

CONCLUSIONS

These results indicate that our animal system is suitable for the amplification of patient tumors and will therefore be beneficial for both in vivo and in vitro assessments and preclinical trials of chemotherapeutics. This has the potential to provide a very effective tool for future personalized therapy and for conducting translational lung cancer research.

Target concentration dependence of DNA melting temperature on oligonucleotide microarrays

The design of microarrays is currently based on studies focusing on DNA hybridization reaction in bulk solution. However, the presence of a surface to which the probe strand is attached can make the solution-based approximations invalid, resulting in sub-optimum hybridization conditions. To determine the effect of surfaces on DNA duplex formation, the authors studied the dependence of DNA melting temperature (T(m)) on target concentration. An automated system was developed to capture the melting profiles of a 25-mer perfect-match probe-target pair initially hybridized at 23°C. Target concentrations ranged from 0.0165 to 15 nM with different probe amounts (0.03-0.82 pmol on a surface area of 10(18) Å(2)), a constant probe density (5 × 10(12) molecules/cm(2)) and spacer length (15 dT). The authors found that T(m) for duplexes anchored to a surface is lower than in-solution, and this difference increases with increasing target concentration. In a representative set, a target concentration increase from 0.5 to 15 nM with 0.82 pmol of probe on the surface resulted in a T(m) decrease of 6°C when compared with a 4°C increase in solution. At very low target concentrations, a multi-melting process was observed in low temperature domains of the curves. This was attributed to the presence of truncated or mismatch probes.

Molecular biology of lung cancer: clinical implications

Lung cancer is a heterogeneous disease clinically, biologically, histologically, and molecularly. Understanding the molecular causes of this heterogeneity, which might reflect changes occurring in different classes of epithelial cells or different molecular changes occurring in the same target lung epithelial cells, is the focus of current research. Identifying the genes and pathways involved, determining how they relate to the biological behavior of lung cancer, and their utility as diagnostic and therapeutic targets are important basic and translational research issues. This article reviews current information on the key molecular steps in lung cancer pathogenesis, their timing, and clinical implications.

A pathway-based approach to identify molecular biomarkers in cancer

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Factors associated with the development of brain metastases: analysis of 975 patients with early stage nonsmall cell lung cancer

BACKGROUND

The risk of developing brain metastases after definitive treatment of locally advanced nonsmall cell lung cancer (NSCLC) is approximately 30%-50%. The risk for patients with early stage disease is less defined. The authors sought to investigate this further and to study potential risk factors.

METHODS

The records of all patients who underwent surgery for T1-T2 N0-N1 NSCLC at Duke University between the years 1995 and 2005 were reviewed. The cumulative incidence of brain metastases and distant metastases was estimated by using the Kaplan-Meier method. A multivariate analysis assessed factors associated with the development of brain metastases.

RESULTS

Of 975 consecutive patients, 85% were stage I, and 15% were stage II. Adjuvant chemotherapy was given to 7%. The 5-year actuarial risk of developing brain metastases and distant metastases was 10%(95% confidence interval [CI], 8-13) and 34%(95% CI, 30-39), respectively. Of patients developing brain metastases, the brain was the sole site of failure in 43%. On multivariate analysis, younger age (hazard ratio [HR], 1.03 per year), larger tumor size (HR, 1.26 per cm), lymphovascular space invasion (HR, 1.87), and hilar lymph node involvement (HR, 1.18) were associated with an increased risk of developing brain metastases.

CONCLUSIONS

In this large series of patients treated surgically for early stage NSCLC, the 5-year actuarial risk of developing brain metastases was 10%. A better understanding of predictive factors and biological susceptibility is needed to identify the subset of patients with early stage NSCLC who are at particularly high risk.

Multigene expression-based predictors for sensitivity to Vorinostat and Velcade in non-small cell lung cancer

The ability to predict the efficacy of molecularly targeted therapies for non-small cell lung cancer (NSCLC) for an individual patient remains problematic. The purpose of this study was to identify, using a refined "coexpression extrapolation (COXEN)" algorithm with a continuous spectrum of drug activity, tumor biomarkers that predict drug sensitivity and therapeutic efficacy in NSCLC to Vorinostat, a histone deacetylase inhibitor, and Velcade, a proteasome inhibitor. Using our refined COXEN algorithm, biomarker prediction models were discovered and trained for Vorinostat and Velcade based on the in vitro drug activity profiles of nine NSCLC cell lines (NCI-9). Independently, a panel of 40 NSCLC cell lines (UVA-40) were treated with Vorinostat or Velcade to obtain 50% growth inhibition values. Genome-wide expression profiles for both the NCI-9 and UVA-40 cell lines were determined using the Affymetrix HG-U133A platform. Modeling generated multigene expression signatures for Vorinostat (45-gene; P = 0.002) and Velcade (15-gene; P = 0.0002), with one overlapping gene (CFLAR). Examination of Vorinostat gene ontogeny revealed a predilection for cellular replication and death, whereas that of Velcade suggested involvement in cellular development and carcinogenesis. Multivariate regression modeling of the refined COXEN scores significantly predicted the activity of combination therapy in NSCLC cells (P = 0.007). Through the refinement of the COXEN algorithm, we provide an in silico method to generate biomarkers that predict tumor sensitivity to molecularly targeted therapies. Use of this refined COXEN method has significant implications for the a priori examination of targeted therapies to more effectively streamline subsequent clinical trial design and cost.

Utility of functional imaging in prediction or assessment of treatment response and prognosis following thermotherapy

The purpose of this review is to examine the roles that functional imaging may play in prediction of treatment response and determination of overall prognosis in patients who are enrolled in thermotherapy trials, either in combination with radiotherapy, chemotherapy or both. Most of the historical work that has been done in this field has focused on magnetic resonance imaging/magnetic resonance spectroscopy (MRI/MRS) methods, so the emphasis will be there, although some discussion of the role that positron emission tomography (PET) might play will also be examined. New optical technologies also hold promise for obtaining low cost, yet valuable physiological data from optically accessible sites. The review is organised by traditional outcome parameters: local response, local control and progression-free or overall survival. Included in the review is a discussion of future directions for this type of translational work.

Predictive biomarker validation in practice: lessons from real trials

BACKGROUND

With the advent of targeted therapies, biomarkers provide a promising means of individualizing therapy through an integrated approach to prediction using the genetic makeup of the disease and the genotype of the patient. Biomarker validation has therefore become a central topic of discussion in the field of medicine, primarily due to the changing landscape of therapies for treatment of a disease and these therapies purported mechanism(s) of action.

PURPOSE

In this report, we discuss the merits and limitations of some of the clinical trial designs for predictive biomarker validation using examples from ongoing or completed clinical trials.

METHODS

The designs are broadly classified as retrospective (i.e., using data from previously well-conducted randomized controlled trials (RCT)) versus prospective (enrichment or targeted, unselected or all-comers, hybrid, and adaptive analysis). We discuss some of these designs in the context of real trials.

RESULTS

Well-designed retrospective analysis of prospective RCT can bring forward effective treatments to marker defined subgroup of patients in a timely manner. An example is the KRAS gene status in colorectal cancer - the benefit from cetuximab and panitumumab was demonstrated to be restricted to patients with wild type status based on prospectively specified analyses using data from previously conducted RCTs. Prospective enrichment designs are appropriate when compelling preliminary evidence suggests that not all patients will benefit from the study treatment under consideration; however, this may sometimes leave questions unanswered. An example is the established benefit of trastuzumab as adjuvant therapy for breast cancer; a clear definition of HER2-positivity and the assay reproducibility have, however, remained unanswered. An all-comers design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (e.g., EGFR expression and tyrosine kinase inhibitors in lung cancer), or to identify the most effective therapy from a panel of regimens (e.g., chemotherapy options in breast cancer).

LIMITATIONS

The designs discussed here rest on the assumption that the technical feasibility, assay performance metrics, and the logistics of specimen collection are well established and that initial results demonstrate promise with regard to the predictive ability of the marker(s).

CONCLUSIONS

The choice of a clinical trial design is driven by a combination of scientific, clinical, statistical, and ethical considerations. There is no one size fits all solution to predictive biomarker validation.

Patient-derived first generation xenografts of non-small cell lung cancers: promising tools for predicting drug responses for personalized chemotherapy

PURPOSE

Current chemotherapeutic regimens have only modest benefit for non-small cell lung cancer (NSCLC) patients. Cumulative toxicities/drug resistance limit chemotherapy given after the first-line regimen. For personalized chemotherapy, clinically relevant NSCLC models are needed for quickly predicting the most effective regimens for therapy with curative intent. In this study, first generation subrenal capsule xenografts of primary NSCLCs were examined for (a) determining responses to conventional chemotherapeutic regimens and (b) selecting regimens most effective for individual patients.

EXPERIMENTAL DESIGN

Pieces (1x3x3 mm(3)) of 32 nontreated, completely resected patients' NSCLCs were grafted under renal capsules of nonobese diabetic/severe combined immunodeficient mice and treated with (A) cisplatin+vinorelbine, (B) cisplatin+docetaxel, (C) cisplatin+gemcitabine, and positive responses (treated tumor area <or=50% of control, P < 0.05) were determined. Clinical outcomes of treated patients were acquired.

RESULTS

Xenografts from all NSCLCs were established (engraftment rate, 90%) with the retention of major biological characteristics of the original cancers. The entire process of drug assessment took 8 weeks. Response rates to regimens A, B, and C were 28% (9 of 32), 42% (8 of 19), and 44% (7 of 16), respectively. Certain cancers that were resistant to a particular regimen were sensitive to others. The majority of responsive tumors contained foci of nonresponding cancer cells, indicative of tumor heterogeneity and potential drug resistance. Xenografts from six of seven patients who developed recurrence/metastasis were nonresponsive.

CONCLUSIONS

Models based on first generation NSCLC subrenal capsule xenografts have been developed, which are suitable for quick assessment (6-8 weeks) of the chemosensitivity of patients' cancers and selection of the most effective regimens. They hold promise for application in personalized chemotherapy of NSCLC patients.

Genomic advances and their impact on clinical trial design

Medical treatment for patients has historically been based on two primary elements: the expected outcome for the patient, and the ability of treatment to improve the expected outcome. The advance in genomic technologies has the potential to change this paradigm and add substantial value to current medical practice by providing an integrated approach to guide patient-specific treatment selection using the genetic make-up of the disease and the genotype of the patient. Specifically, genomic signatures can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), and/or in differential diagnosis (identifying who is likely to respond to which drug(s)). Several critical issues, including scientific rationale, clinical trial design, marker assessment methods, cost and feasibility have to be carefully considered in the validation of biomarkers through clinical research before they can be routinely integrated into clinical practice. Here, we highlight the impact of genomic advances on various aspects of clinical trial design.