Co-clinical trials demonstrate superiority of crizotinib to chemotherapy in ALK-rearranged non-small cell lung cancer and predict strategies to overcome resistance

Six-Gene Signature for Differential Diagnosis and Therapeutic Decisions in Non-Small-Cell Lung Cancer-A Validation Study

Non-small-cell lung cancer (NSCLC) poses a challenge due to its heterogeneity, necessitating precise histopathological subtyping and prognostication for optimal treatment decision-making. Molecular markers emerge as a potential solution, overcoming the limitations of conventional methods and supporting the diagnostic-therapeutic interventions. In this study, we validated the expression of six genes (MIR205HG, KRT5, KRT6A, KRT6C, SERPINB5, and DSG3), previously identified within a 53-gene signature developed by our team, utilizing gene expression microarray technology. Real-time PCR on 140 thoroughly characterized early-stage NSCLC samples revealed substantial upregulation of all six genes in squamous cell carcinoma (SCC) compared to adenocarcinoma (ADC), regardless of clinical factors. The decision boundaries of the logistic regression model demonstrated effective separation of the relative expression levels between SCC and ADC for most genes, excluding KRT6C. Logistic regression and gradient boosting decision tree classifiers, incorporating all six validated genes, exhibited notable performance (AUC: 0.8930 and 0.8909, respectively) in distinguishing NSCLC subtypes. Nevertheless, our investigation revealed that the gene expression profiles failed to yield predictive value regarding the progression of early-stage NSCLC. Our molecular diagnostic models manifest the potential for an exhaustive molecular characterization of NSCLC, subsequently informing personalized treatment decisions and elevating the standards of clinical management and prognosis for patients.

EML4-ALK fusions drive lung adeno-to-squamous transition through JAK-STAT activation

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, exhibits strong cancer plasticity. We find that ALK rearrangement is detectable in 5.1-7.5% of human LUAS, and transgenic expression of EML4-ALK drives lung adenocarcinoma (LUAD) formation initially and squamous transition at late stage. We identify club cells as the main cell-of-origin for squamous transition. Through recapitulating lineage transition in organoid system, we identify JAK-STAT signaling, activated by EML4-ALK phase separation, significantly promotes squamous transition. Integrative study with scRNA-seq and immunostaining identify a plastic cell subpopulation in ALK-rearranged human LUAD showing squamous biomarker expression. Moreover, those relapsed ALK-rearranged LUAD show notable upregulation of squamous biomarkers. Consistently, mouse squamous tumors or LUAD with squamous signature display certain resistance to ALK inhibitor, which can be overcome by combined JAK1/2 inhibitor treatment. This study uncovers strong plasticity of ALK-rearranged tumors in orchestrating phenotypic transition and drug resistance and proposes a potentially effective therapeutic strategy.

Deterministic reprogramming and signaling activation following targeted therapy in non-small cell lung cancer driven by mutations or oncogenic fusions

INTRODUCTION

Targeted therapy is used to treat lung adenocarcinoma caused by epidermal growth factor receptor (EGFR) mutations in the tyrosine kinase domain and rare subtypes (<5%) of non-small cell lung cancer. These subtypes include fusion oncoproteins like anaplastic lymphoma kinase (ALK), ROS1, rearranged during transfection (RET), and other receptor tyrosine kinases (RTKs). The use of diverse selective oral inhibitors, including those targeting rat sarcoma viral oncogene homolog (KRAS) mutations, has significantly improved clinical responses, extending progression-free and overall survival.

AREAS COVERED

Resistance remains a critical issue in lung adenocarcinoma, notably in EGFR mutant, echinoderm microtubule associated protein-like 4 (EML4)-ALK fusion, and KRAS mutant tumors, often associated with epithelial-to-mesenchymal transition (EMT).

EXPERT OPINION

Despite advancements in next generation EGFR inhibitors and EML4-ALK therapies with enhanced brain penetrance and identifying resistance mutations, overcoming resistance has not been abated. Various strategies are being explored to overcome this issue to achieve prolonged cancer remission and delay resistance. Targeting yes-associated protein (YAP) and the mechanisms associated with YAP activation through Hippo-dependent or independent pathways, is desirable. Additionally, the exploration of liquid-liquid phase separation in fusion oncoproteins forming condensates in the cytoplasm for oncogenic signaling is a promising field for the development of new treatments.

A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

Lenvatinib, a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer, facing limitations due to drug resistance. Here, we applied a multidimensional, high-throughput screening platform comprising patient-derived resistant liver tumor cells (PDCs), organoids (PDOs), and xenografts (PDXs) to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings. Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment, expediting drug repurposing screens. Pharmacological screening identified romidepsin, YM155, apitolisib, NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models. Notably, romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway. A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models. Collectively, our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer, providing a feasible multidimensional platform for personalized medicine.

miRNA-Seq Tissue Diagnostic Signature: A Novel Model for NSCLC Subtyping

Non-small cell lung cancer (NSCLC) encompasses distinct histopathological subtypes, namely adenocarcinoma (AC) and squamous cell lung carcinoma (SCC), which require precise differentiation for effective treatment strategies. In this study, we present a novel molecular diagnostic model that integrates tissue-specific expression profiles of microRNAs (miRNAs) obtained through next-generation sequencing (NGS) to discriminate between AC and SCC subtypes of NSCLC. This approach offers a more comprehensive and precise molecular characterization compared to conventional methods such as histopathology or immunohistochemistry. Firstly, we identified 31 miRNAs with significant differential expression between AC and SCC cases. Subsequently, we constructed a 17-miRNA signature through rigorous multistep analyses, including LASSO/elastic net regression. The signature includes both upregulated miRNAs (hsa-miR-326, hsa-miR-450a-5p, hsa-miR-1287-5p, hsa-miR-556-5p, hsa-miR-542-3p, hsa-miR-30b-5p, hsa-miR-4728-3p, hsa-miR-450a-1-3p, hsa-miR-375, hsa-miR-147b, hsa-miR-7705, and hsa-miR-653-3p) and downregulated miRNAs (hsa-miR-944, hsa-miR-205-5p, hsa-miR-205-3p, hsa-miR-149-5p, and hsa-miR-6510-3p). To assess the discriminative capability of the 17-miRNA signature, we performed receiver operating characteristic (ROC) curve analysis, which demonstrated an impressive area under the curve (AUC) value of 0.994. Our findings highlight the exceptional diagnostic performance of the miRNA signature as a stratifying biomarker for distinguishing between AC and SCC subtypes in lung cancer. The developed molecular diagnostic model holds promise for providing a more accurate and comprehensive molecular characterization of NSCLC, thereby guiding personalized treatment decisions and improving clinical management and prognosis for patients.

Harnessing preclinical models for the interrogation of ovarian cancer

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

A new ALK inhibitor overcomes resistance to first- and second-generation inhibitors in NSCLC

More than 60% of nonsmall cell lung cancer (NSCLC) patients show a positive response to the first ALK inhibitor, crizotinib, which has been used as the standard treatment for newly diagnosed patients with ALK rearrangement. However, most patients inevitably develop crizotinib resistance due to acquired secondary mutations in the ALK kinase domain, such as the gatekeeper mutation L1196M and the most refractory mutation, G1202R. Here, we develop XMU-MP-5 as a new-generation ALK inhibitor to overcome crizotinib resistance mutations, including L1196M and G1202R. XMU-MP-5 blocks ALK signaling pathways and inhibits the proliferation of cells harboring either wild-type or mutant EML4-ALK in vitro and suppresses tumor growth in xenograft mouse models in vivo. Structural analysis provides insights into the mode of action of XMU-MP-5. In addition, XMU-MP-5 induces significant regression of lung tumors in two genetically engineered mouse (GEM) models, further demonstrating its pharmacological efficacy and potential for clinical application. These preclinical data support XMU-MP-5 as a novel selective ALK inhibitor with high potency and selectivity. XMU-MP-5 holds great promise as a new therapeutic against clinically relevant secondary ALK mutations.

Preclinical Models for the Study of Lung Cancer Pathogenesis and Therapy Development

Experimental preclinical models have been a cornerstone of lung cancer translational research. Work in these model systems has provided insights into the biology of lung cancer subtypes and their origins, contributed to our understanding of the mechanisms that underlie tumor progression, and revealed new therapeutic vulnerabilities. Initially patient-derived lung cancer cell lines were the main preclinical models available. The landscape is very different now with numerous preclinical models for research each with unique characteristics. These include genetically engineered mouse models (GEMMs), patient-derived xenografts (PDXs) and three-dimensional culture systems ("organoid" cultures). Here we review the development and applications of these models and describe their contributions to lung cancer research.

Exploring liver cancer biology through functional genetic screens

As the fourth leading cause of cancer-related death in the world, liver cancer poses a major threat to human health. Although a growing number of therapies have been approved for the treatment of hepatocellular carcinoma in the past few years, most of them only provide a limited survival benefit. Therefore, an urgent need exists to identify novel targetable vulnerabilities and powerful drug combinations for the treatment of liver cancer. The advent of functional genetic screening has contributed to the advancement of liver cancer biology, uncovering many novel genes involved in tumorigenesis and cancer progression in a high-throughput manner. In addition, this unbiased screening platform also provides an efficient tool for the exploration of the mechanisms involved in therapy resistance as well as identifying potential targets for therapy. In this Review, we describe how functional screens can help to deepen our understanding of liver cancer and guide the development of new therapeutic strategies.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer

Purpose

We sought to exploit the heterogeneity afforded by patient-derived tumor xenografts (PDX) to first, optimize and identify robust radiomic features to predict response to therapy in subtype-matched triple negative breast cancer (TNBC) PDX, and second, to implement PDX-optimized image features in a TNBC co-clinical study to predict response to therapy using machine learning (ML) algorithms.

Methods

TNBC patients and subtype-matched PDX were recruited into a co-clinical FDG-PET imaging trial to predict response to therapy. One hundred thirty-one imaging features were extracted from PDX and human-segmented tumors. Robust image features were identified based on reproducibility, cross-correlation, and volume independence. A rank importance of predictors using ReliefF was used to identify predictive radiomic features in the preclinical PDX trial in conjunction with ML algorithms: classification and regression tree (CART), Naïve Bayes (NB), and support vector machines (SVM). The top four PDX-optimized image features, defined as radiomic signatures (RadSig), from each task were then used to predict or assess response to therapy. Performance of RadSig in predicting/assessing response was compared to SUV_mean, SUV_max, and lean body mass-normalized SUL_peak measures.

Results

Sixty-four out of 131 preclinical imaging features were identified as robust. NB-RadSig performed highest in predicting and assessing response to therapy in the preclinical PDX trial. In the clinical study, the performance of SVM-RadSig and NB-RadSig to predict and assess response was practically identical and superior to SUV_mean, SUV_max, and SUL_peak measures.

Conclusions

We optimized robust FDG-PET radiomic signatures (RadSig) to predict and assess response to therapy in the context of a co-clinical imaging trial.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05489-8.

Deep Learning Segmentation of Triple-Negative Breast Cancer (TNBC) Patient Derived Tumor Xenograft (PDX) and Sensitivity of Radiomic Pipeline to Tumor Probability Boundary

Simple Summary

Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical trial to inform the corresponding clinical trial. The preclinical arm aids in assessing therapeutic efficacy, patient stratification, and designing optimal imaging strategies. There is much interest in harmonizing preclinical and clinical quantitative imaging pipelines. Radiomics is widely explored in clinical imaging to predict response to therapy. In preclinical imaging, high-throughput radiomic analysis is limited by manual delineation of tumor boundaries, which is labor intensive with poor reproducibility. Our proposed deep-learning-based system was trained to automatically segment tumors from multi-contrast MR images and extract radiomic features. The proposed method is highly reproducible with significant correlation in radiomic features. The deployment of this pipeline in the preclinical arm would provide high throughput and reproducible radiomic analysis.

Abstract

Preclinical magnetic resonance imaging (MRI) is a critical component in a co-clinical research pipeline. Importantly, segmentation of tumors in MRI is a necessary step in tumor phenotyping and assessment of response to therapy. However, manual segmentation is time-intensive and suffers from inter- and intra- observer variability and lack of reproducibility. This study aimed to develop an automated pipeline for accurate localization and delineation of TNBC PDX tumors from preclinical T1w and T2w MR images using a deep learning (DL) algorithm and to assess the sensitivity of radiomic features to tumor boundaries. We tested five network architectures including U-Net, dense U-Net, Res-Net, recurrent residual UNet (R2UNet), and dense R2U-Net (D-R2UNet), which were compared against manual delineation by experts. To mitigate bias among multiple experts, the simultaneous truth and performance level estimation (STAPLE) algorithm was applied to create consensus maps. Performance metrics (F1-Score, recall, precision, and AUC) were used to assess the performance of the networks. Multi-contrast D-R2UNet performed best with F1-score = 0.948; however, all networks scored within 1–3% of each other. Radiomic features extracted from D-R2UNet were highly corelated to STAPLE-derived features with 67.13% of T1w and 53.15% of T2w exhibiting correlation ρ ≥ 0.9 (p ≤ 0.05). D-R2UNet-extracted features exhibited better reproducibility relative to STAPLE with 86.71% of T1w and 69.93% of T2w features found to be highly reproducible (CCC ≥ 0.9, p ≤ 0.05). Finally, 39.16% T1w and 13.9% T2w features were identified as insensitive to tumor boundary perturbations (Spearman correlation (−0.4 ≤ ρ ≤ 0.4). We developed a highly reproducible DL algorithm to circumvent manual segmentation of T1w and T2w MR images and identified sensitivity of radiomic features to tumor boundaries.

Co-Clinical Trials: An Innovative Drug Development Platform for Cholangiocarcinoma

Cholangiocarcinoma (CCA), a group of malignancies that originate from the biliary tract, is associated with a high mortality rate and a concerning increase in worldwide incidence. In Thailand, where the incidence of CCA is the highest, the socioeconomic burden is severe. Yet, treatment options are limited, with surgical resection being the only form of treatment with curative intent. The current standard-of-care remains adjuvant and palliative chemotherapy which is ineffective in most patients. The overall survival rate is dismal, even after surgical resection and the tumor heterogeneity further complicates treatment. Together, this makes CCA a significant burden in Southeast Asia. For effective management of CCA, treatment must be tailored to each patient, individually, for which an assortment of targeted therapies must be available. Despite the increasing numbers of clinical studies in CCA, targeted therapy drugs rarely get approved for clinical use. In this review, we discuss the shortcomings of the conventional clinical trial process and propose the implementation of a novel concept, co-clinical trials to expedite drug development for CCA patients. In co-clinical trials, the preclinical studies and clinical trials are conducted simultaneously, thus enabling real-time data integration to accurately stratify and customize treatment for patients, individually. Hence, co-clinical trials are expected to improve the outcomes of clinical trials and consequently, encourage the approval of targeted therapy drugs. The increased availability of targeted therapy drugs for treatment is expected to facilitate the application of precision medicine in CCA.

Preclinical Metrics Correlate With Drug Activity in Phase II Trials of Targeted Therapies for Non-Small Cell Lung Cancer

Novel oncology drugs often fail to progress from preclinical experiments to FDA approval. Therefore, determining which preclinical or clinical factors associate with drug activity could accelerate development of effective therapies. We investigated whether preclinical metrics and patient characteristics are associated with objective response rate (ORR) in phase II clinical trials of targeted therapies for non-small cell lung cancer (NSCLC). We developed a reproducible process to select a single phase II trial and supporting preclinical publication for a given drug-indication pair, which we defined as the pairing of a small molecule inhibitor (e.g., crizotinib) with the specific patient population for which it was designed to work (e.g., patients with an ALK aberration). We demonstrated that robust drug activity in mice, as measured by change in tumor size, is independently associated with improved ORR in phase II clinical trials. The number of mice utilized in experiments, the number of publications referencing the drug for NSCLC before the phase II clinical trial, and whether the drug was approved for a cancer other than NSCLC also significantly correlated with ORR. Among clinical characteristics, sex, race, histology, and smoking history were significantly associated with ORR. Further research into metrics that correlate with drug activity has the potential to optimize selection of novel therapies for clinical trials and enrich the drug development pipeline, particularly for patients with targetable genetic aberrations and rare cancers.

Optimal co-clinical radiomics: Sensitivity of radiomic features to tumour volume, image noise and resolution in co-clinical T1-weighted and T2-weighted magnetic resonance imaging

Background

Radiomics analyses has been proposed to interrogate the biology of tumour as well as to predict/assess response to therapy in vivo. The objective of this work was to assess the sensitivity of radiomics features to noise, resolution, and tumour volume in the context of a co-clinical trial.

Methods

Triple negative breast cancer (TNBC) patients were recruited into an ongoing co-clinical imaging trial. Sub-typed matched TNBC patient-derived tumour xenografts (PDX) were generated to investigate optimal co-clinical MR radiomic features. The MR imaging protocol included T1-weighed and T2-weighted imaging. To test the sensitivity of radiomics to resolution, PDX were imaged at three different resolutions. Multiple sets of images with varying signal-to-noise ratio (SNR) were generated, and an image independent patch-based method was implemented to measure the noise levels. Forty-eight radiomic features were extracted from manually segmented 2D and 3D segmented tumours and normal tissues of T1- and T2- weighted co-clinical MR images.

Findings

Sixteen radiomics features were identified as volume dependent and corrected for volume-dependency following normalization. Features from grey-level run-length matrix (GLRLM), grey-level size zone matrix (GLSZM) were identified as most sensitive to noise. Radiomic features Kurtosis and Run-length variance (RLV) from GLSZM were most sensitive to changes in resolution in both T1w and T2w MRI. In general, 3D radiomic features were more robust compared to 2D (single slice) measures, although the former exhibited higher variability between subjects.

Interpretation

Tumour volume, noise characteristics, and image resolution significantly impact radiomic analysis in co-clinical studies.

Preclinical PERCIST and 25% of SUVmax Threshold: Precision Imaging of Response to Therapy in Co-clinical 18F-FDG PET Imaging of Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts

Numerous recent works highlight the limited utility of established tumor cell lines in recapitulating the heterogeneity of tumors in patients. More realistic preclinical cancer models are thought to be provided by transplantable, patient-derived xenografts (PDXs). The inter- and intratumor heterogeneity of PDXs, however, presents several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics for 18F-FDG PET to assess response to combination docetaxel and carboplatin therapy in a co-clinical trial involving triple-negative breast cancer PDXs. We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. Methods: A test-retest protocol was implemented to optimize the reproducibility of 18F-FDG PET SUV thresholds, SUVpeak metrics, and preclinical PERCIST parameters. In assessing response to therapy, 18F-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. Results: Our data suggest that a threshold of 25% of SUVmax (SUV25) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at α = 0.7 and β = 2.8 and exhibited a high correlation with SUV25 measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. Conclusion: The Quantitative Response Assessment Score favors SUV25 followed by SUVpeak for a sphere with a volume of 14 mm3 (SUVP14) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV25 and preclinical PERCIST SUVP14 as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.

Epigenetics and cell cycle regulation in cystogenesis

The role of genetic mutations in the development of polycystic kidney disease (PKD), such as alterations in PKD1 and PKD2 genes in autosomal dominant PKD (ADPKD), is well understood. However, the significance of epigenetic mechanisms in the progression of PKD remains unclear and is increasingly being investigated. The term of epigenetics describes a range of mechanisms in genome function that do not solely result from the DNA sequence itself. Epigenetic information can be inherited during mammalian cell division to sustain phenotype specifically and physiologically responsive gene expression in the progeny cells. A multitude of functional studies of epigenetic modifiers and systematic genome-wide mapping of epigenetic marks reveal the importance of epigenomic mechanisms, including DNA methylation, histone/chromatin modifications and non-coding RNAs, in PKD pathologies. Deregulated proliferation is a characteristic feature of cystic renal epithelial cells. Moreover, defects in many of the molecules that regulate the cell cycle have been implicated in cyst formation and progression. Recent evidence suggests that alterations of DNA methylation and histone modifications on specific genes and the whole genome involved in cell cycle regulation and contribute to the pathogenesis of PKD. This review summarizes the recent advances of epigenetic mechanisms in PKD, which helps us to define the term of "PKD epigenetics" and group PKD epigenetic changes in three categories. In particularly, this review focuses on the interplay of epigenetic mechanisms with cell cycle regulation during normal cell cycle progression and cystic cell proliferation, and discusses the potential to detect and quantify DNA methylation from body fluids as diagnostic/prognostic biomarkers. Collectively, this review provides concepts and examples of epigenetics in cell cycle regulation to reveal a broad view of different aspects of epigenetics in biology and PKD, which may facilitate to identify possible novel therapeutic intervention points and to explore epigenetic biomarkers in PKD.

Current and Future Horizons of Patient-Derived Xenograft Models in Colorectal Cancer Translational Research

Our poor understanding of the intricate biology of cancer and the limited availability of preclinical models that faithfully recapitulate the complexity of tumors are primary contributors to the high failure rate of novel therapeutics in oncology clinical studies. To address this need, patient-derived xenograft (PDX) platforms have been widely deployed and have reached a point of development where we can critically review their utility to model and interrogate relevant clinical scenarios, including tumor heterogeneity and clonal evolution, contributions of the tumor microenvironment, identification of novel drugs and biomarkers, and mechanisms of drug resistance. Colorectal cancer (CRC) constitutes a unique case to illustrate clinical perspectives revealed by PDX studies, as they overcome limitations intrinsic to conventional ex vivo models. Furthermore, the success of molecularly annotated "Avatar" models for co-clinical trials in other diseases suggests that this approach may provide an additional opportunity to improve clinical decisions, including opportunities for precision targeted therapeutics, for patients with CRC in real time. Although critical weaknesses have been identified with regard to the ability of PDX models to predict clinical outcomes, for now, they are certainly the model of choice for preclinical studies in CRC. Ongoing multi-institutional efforts to develop and share large-scale, well-annotated PDX resources aim to maximize their translational potential. This review comprehensively surveys the current status of PDX models in translational CRC research and discusses the opportunities and considerations for future PDX development.

Afatinib reverses ceritinib resistance (CR) in ALK/ROS1-positive non-small-cell lung cancer cell (NSCLC) via suppression of NRG1 pathway

BACKGROUND

Lung cancer (LC) is the most prevalent malignancy worldwide, and non-small-cell LC (NSCLC) cell is associated with high mortality. As a member of the second generation of anaplastic lymphoma kinase (ALK) suppressors, ceritinib has considerable therapeutic effects for ALK and c-ros oncogene 1 (ROS1)-positive NSCLC cell. Nevertheless, patients inevitably develop resistance to the drug. Our research focused on the exploration of whether afatinib was able to counteract ceritinib resistance (CR) in NSCLC cells with positive ALK or ROS1.

MATERIALS AND METHODS

Acquired CR cell sublines (HCC78R and H1299R) were induced by stepwise escalation of ceritinib exposure. MTT assay was used to validate cell proliferation. Fluorescence assay was performed for apoptosis analysis. Quantitative real-time PCR and Western blot assays were used to assess the alterations of signaling pathway-related mRNA and proteins, respectively.

RESULTS

We found that prolonged treatment of HCC78 and H1299 with ceritinib brought about 10 times weaker ceritinib sensitivity (CS) in comparison with parent cells. Additionally, the results showed that afatinib efficiently promoted CS, which was evidenced as reduced proliferation and cell death promotion, in NSCLC cells, irrespective of their previous sensitivity or resistance to ceritinib. Moreover, afatinib decreased neuregulin-1 (NRG1) signaling stimulation in CR as well as CS cells. Furthermore, supplementing NRG1 in H1299 and HCC78 cells triggered CR, which was attenuated by afatinib.

CONCLUSION

These results demonstrated that afatinib overcame CR in NSCLC cells with positive ALK or ROS1 by inhibiting the NRG1 signaling pathway, which might be a promising therapeutic approach.

Outcomes by EGFR, KRAS, and ALK Genotype After Combined Modality Therapy for Locally Advanced Non–Small-Cell Lung Cancer

Purpose

In 699 patients with locally advanced non–small-cell lung cancer (NSCLC) treated with radiation therapy as part of combined modality therapy, we compared outcomes among genotyped and ungenotyped patients and by tumor genotype status ( EGFR, KRAS, and ALK).

Patients and Methods

Genotyping was performed in 250 patients: EGFR+ (19%), KRAS+ (32%), ALK+ (9%), and wild type (WT−/−/−; 40%). Outcomes were analyzed using the Kaplan-Meier method and Cox regression.

Results

With a median follow-up of 48.2 months among genotyped patients, median overall survival (OS) was significantly longer for EGFR+ and ALK+ compared with KRAS+ and WT−/−/− (55.8 months v not reached v 28.0 v 33.2 months; P = .02). There was no difference in progression-free survival (median, 15.3 v 13.7 v 13.0 v 14.5 months; P = .47) or in freedom from distant metastases by genotype (3-year estimates: 42% v 49% v 27% v 25%; P = .25). There was higher freedom from locoregional recurrence (LRR) for EGFR+ tumors and lower freedom from LRR in ALK+ tumors, compared with KRAS+ and WT−/−/− tumors (3-year: 77% v 38% v 49% v 46%). In multivariable analysis, ALK+ remained associated with increased OS (HR, 0.32; 95% CI, 0.12 to 0.87; P = .03), and EGFR+ was associated with decreased LRR (HR, 0.47; 95% CI, 0.24 to 0.92; P = .03). Analysis of post-recurrence survival demonstrated that EGFR+/ ALK+ patients treated with appropriate tyrosine kinase inhibitors had higher OS compared with other groups.

Conclusion

In this series of locally advanced NSCLC treated with combined modality therapy, EGFR+ and ALK+ were associated with higher OS, whereas LRR was lower in EGFR+ patients, and the risk of distant metastases was high in all subgroups. The outcomes and patterns of failure in genotypic subgroups of NSCLC from this study can inform the design of future trials integrating targeted therapies.

Patient-derived xenograft mouse models: A high fidelity tool for individualized medicine

Patient-derived xenograft (PDX) mouse models involve the direct transfer of fresh human tumor samples into immunodeficient mice following surgical resection or other medical operations. Gene expression in tumors may be maintained by serial passages of tumors from mouse to mouse. These models aid research into tumor biology and pharmacology without manual manipulation of cell cultures in vitro. and are widely used in individualized cancer therapy/translational medicine, drug development and coclinical trials. PDX models exhibit higher predictive values for clinical outcomes than cell line-derived xenograft models and genetically engineered mouse models. However, PDX models are associated with certain challenges in clinical application. The present study reviewed current collections of PDX models and assessed the challenges and future directions of this field.

Autochthonous murine models for the study of smoker and never-smoker associated lung cancers

Lung cancer accounts for the greatest number of cancer deaths in the world. Tobacco smoke-associated cancers constitute the majority of lung cancer cases but never-smoker cancers comprise a significant and increasing fraction of cases. Recent genomic and transcriptomic sequencing efforts of lung cancers have revealed distinct sets of genetic aberrations of smoker and never-smoker lung cancers that implicate disparate biology and therapeutic strategies. Autochthonous mouse models have contributed greatly to our understanding of lung cancer biology and identified novel therapeutic targets and strategies in the era of targeted therapy. With the emergence of immuno-oncology, mouse models may continue to serve as valuable platforms for novel biological insights and therapeutic strategies. Here, we will review the variety of available autochthonous mouse models of lung cancer, their relation to human smoker and never-smoker lung cancers, and their application to immuno-oncology and immune checkpoint blockade that is revolutionizing lung cancer therapy.

Preclinical and Coclinical Studies in Prostate Cancer

Men who develop metastatic castration-resistant prostate cancer (mCRPC) will invariably succumb to their disease. Thus there remains a pressing need for preclinical testing of new drugs and drug combinations for late-stage prostate cancer (PCa). Insights from the mCRPC genomic landscape have revealed that, in addition to sustained androgen receptor (AR) signaling, there are other actionable molecular alterations and distinct molecular subclasses of PCa; however, the rate at which this knowledge translates into patient care via current preclinical testing is painfully slow and inefficient. Here, we will highlight the issues involved and discuss a new translational platform, "the co-clinical trial project," to expedite current preclinical studies and optimize clinical trial and experimental drug testing. With this platform, in vivo preclinical and early clinical studies are closely aligned, enabling in vivo testing of drugs using genetically engineered mouse models (GEMMs) in defined genetic contexts to personalize individual therapies. We will discuss the principles and essential components of this novel paradigm, representative success stories and future therapeutic options for mCRPC that should be explored.

Suppression of Adaptive Responses to Targeted Cancer Therapy by Transcriptional Repression

Acquired drug resistance is a major factor limiting the effectiveness of targeted cancer therapies. Targeting tumors with kinase inhibitors induces complex adaptive programs that promote the persistence of a fraction of the original cell population, facilitating the eventual outgrowth of inhibitor-resistant tumor clones. We show that the addition of a newly identified CDK7/12 inhibitor, THZ1, to targeted therapy enhances cell killing and impedes the emergence of drug-resistant cell populations in diverse cellular and in vivo cancer models. We propose that targeted therapy induces a state of transcriptional dependency in a subpopulation of cells poised to become drug tolerant, which THZ1 can exploit by blocking dynamic transcriptional responses, promoting remodeling of enhancers and key signaling outputs required for tumor cell survival in the setting of targeted therapy. These findings suggest that the addition of THZ1 to targeted therapies is a promising broad-based strategy to hinder the emergence of drug-resistant cancer cell populations.Significance: CDK7/12 inhibition prevents active enhancer formation at genes, promoting resistance emergence in response to targeted therapy, and impedes the engagement of transcriptional programs required for tumor cell survival. CDK7/12 inhibition in combination with targeted cancer therapies may serve as a therapeutic paradigm for enhancing the effectiveness of targeted therapies. Cancer Discov; 8(1); 59-73. ©2017 AACR.See related commentary by Carugo and Draetta, p. 17This article is highlighted in the In This Issue feature, p. 1.

Serum Metabolic Profile Alteration Reveals Response to Platinum-Based Combination Chemotherapy for Lung Cancer: Sensitive Patients Distinguished from Insensitive ones

Most lung cancers are diagnosed at fairly advanced stages due to limited clinical symptoms. Platinum-based chemotherapy, either as single regimen or in combination with radiation, is one of the major recommendations for the patients. Earlier evaluation of the effectiveness of the chemotherapies is critical for developing better treatment plan given the toxicity of the chemotherapeutic reagents. Drug efficacy could be reflected in the systemic metabolism characteristics though knowledge about which remains scarce. In this study, serum metabolism influence of three types of commonly used platinum-based combination chemotherapy regimens, namely cisplatin with gemcitabine, vinorelbine or docetaxel, were studied using pattern recognition coupled with nuclear magnetic resonance techniques. The treated patients were divided into sensitive or insensitive subgroups according to their response to the treatments. We found that insensitive subjects can be identified from the sensitive ones with up-regulation of glucose and taurine but reduced alanine and lactate concentrations in serum. The combination chemotherapy of lung cancer is accompanied by disturbances of multiple metabolic pathways such as energy metabolism, phosphatidylcholine biosynthesis, so that the treated patients were marginally discriminated from the untreated. Serum metabolic profile of patients shows potential as an indicator of their response to platinum-based combination chemotherapy.

Molecular mechanism and targeted therapy of Hsp90 involved in lung cancer: New discoveries and developments (Review)

The exploration of the molecular mechanisms and signaling pathways on lung cancer is very important for developing new strategies of diagnosis and treatment to this disease, such as finding valuable lung cancer markers and molecularly targeted therapies. Previously, a number of studies disclose that heat shock protein 90 (Hsp90) is upregulated in cancer cells, tissues and serum of lung cancer patients, and its upregulation intimately correlates with the occurrence, development and outcome of lung cancer. On the contrary, inhibition of Hsp90 can suppress cell proliferation, motility and metastasis of lung cancer and promote apoptosis of lung cancer cells via complex signaling pathways. In addition, a series of Hsp90 inhibitors have been investigated as effective molecular targeted therapy tactics fighting against lung cancer. This review, systematically summarizes the role of Hsp90 in lung cancer, the molecular mechanisms and development of anti-Hsp90 treatment in lung cancer.

Crizotinib resistance: implications for therapeutic strategies

In 2007, a chromosomal rearrangement resulting in a gene fusion leading to expression of a constitutively active anaplastic lymphoma kinase (ALK) fusion protein was identified as an oncogenic driver in non-small-cell lung cancer (NSCLC). ALK rearrangements are detected in 3%-7% of patients with NSCLC and are particularly enriched in younger patients with adenocarcinoma and a never or light smoking history. Fortuitously, crizotinib, a small molecule tyrosine kinase inhibitor initially developed to target cMET, was able to be repurposed for ALK-rearranged (ALK+) NSCLC. Despite dramatic and durable initial responses to crizotinib; however, the vast majority of patients will develop resistance within a few years. Diverse molecular mechanisms underlie resistance to crizotinib. This review will describe the clinical activity of crizotinib, review identified mechanisms of crizotinib resistance, and end with a survey of emerging therapeutic strategies aimed at overcoming crizotinib resistance.

The role of the ALK receptor in cancer biology

A vast array of oncogenic variants has been identified for anaplastic lymphoma kinase (ALK). Therefore, there is a need to better understand the role of ALK in cancer biology in order to optimise treatment strategies. This review summarises the latest research on the receptor tyrosine kinase ALK, and how this information can guide the management of patients with cancer that is ALK-positive. A variety of ALK gene alterations have been described across a range of tumour types, including point mutations, deletions and rearrangements. A wide variety of ALK fusions, in which the kinase domain of ALK and the amino-terminal portion of various protein partners are fused, occur in cancer, with echinoderm microtubule-associated protein-like 4 (EML4)-ALK being the most prevalent in non-small-cell lung cancer (NSCLC). Different ALK fusion proteins can mediate different signalling outputs, depending on properties such as subcellular localisation and protein stability. The ALK fusions found in tumours lack spatial and temporal regulation, which can also affect dimerisation and substrate specificity. Two ALK tyrosine kinase inhibitors (TKIs), crizotinib and ceritinib, are currently approved in Europe for use in ALK-positive NSCLC and several others are in development. These ALK TKIs bind slightly differently within the ATP-binding pocket of the ALK kinase domain and are associated with the emergence of different resistance mutation patterns during therapy. This emphasises the need to tailor the sequence of ALK TKIs according to the ALK signature of each patient. Research into the oncogenic functions of ALK, and fast paced development of ALK inhibitors, has substantially improved outcomes for patients with ALK-positive NSCLC. Limited data are available surrounding the physiological ligand-stimulated activation of ALK signalling and further research is needed. Understanding the role of ALK in tumour biology is key to further optimising therapeutic strategies for ALK-positive disease.

Co-clinical quantitative tumor volume imaging in ALK-rearranged NSCLC treated with crizotinib

PURPOSE

To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC).

METHODS

Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans.

RESULTS

The median tumor volume decrease (%) at the maximal response was -40.4% (range: -79.5%-+11.7%) in mice, and -72.9% (range: -100%-+72%) in humans (Wilcoxon p=0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months.

CONCLUSION

The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.

Preclinical Modeling of KIF5B-RET Fusion Lung Adenocarcinoma

RET fusions have been found in lung adenocarcinoma, of which KIF5B-RET is the most prevalent. We established inducible KIF5B-RET transgenic mice and KIF5B-RET-dependent cell lines for preclinical modeling of KIF5B-RET-associated lung adenocarcinoma. Doxycycline-induced CCSP-rtTA/tetO-KIF5B-RET transgenic mice developed invasive lung adenocarcinoma with desmoplastic reaction. Tumors regressed upon suppression of KIF5B-RET expression. By culturing KIF5B-RET-dependent BaF3 (B/KR) cells with increasing concentrations of cabozantinib or vandetanib, we identified cabozantinib-resistant RET^V804L mutation and vandetanib-resistant-RET^G810A mutation. Among cabozantinib, lenvatinib, ponatinib, and vandetanib, ponatinib was identified as the most potent inhibitor against KIF5B-RET and its drug-resistant mutants. Interestingly, the vandetanib-resistant KIF5B-RET^G810A mutant displayed gain-of-sensitivity (GOS) to ponatinib and lenvatinib. Treatment of doxycycline-induced CCSP-rtTA/tetO-KIF5B-RET bitransgenic mice with ponatinib effectively induced tumor regression. These results indicate that KIF5B-RET-associated lung tumors are addicted to the fusion oncogene and ponatinib is the most effective inhibitor for targeting KIF5B-RET in lung adenocarcinoma. Moreover, this study finds a novel vandetanib-resistant RET^G810A mutation and identifies lenvatinib and ponatinib as the secondary drugs to overcome this vandetanib resistance mechanism. Mol Cancer Ther; 15(10); 2521-9. ©2016 AACR.

The steady progress of targeted therapies, promising advances for lung cancer

Lung cancer remains one of the most complex and challenging cancers, being responsible for almost a third of all cancer deaths. This grim picture seems however to be changing, for at least a subset of lung cancers. The number of patients who can benefit from targeted therapies is steadily increasing thanks to the progress made in identifying actionable driver lesions in lung tumours. The success of the latest generation of EGFR and ALK inhibitors in the clinic not only illustrates the value of targeted therapies, but also shows how almost inevitably drug resistance develops. Therefore, more sophisticated approaches are needed to achieve long-term remissions. Although there are still significant barriers to be overcome, technological advances in early detection of relevant mutations and the opportunity to test new drugs in predictive preclinical models justify the hope that we will overcome these obstacles.

Efficacy of targeted AKT inhibition in genetically engineered mouse models of PTEN-deficient prostate cancer

The PI3K/AKT pathway is frequently altered in advanced human prostate cancer mainly through the loss of functional PTEN, and presents as potential target for personalized therapy. Our aim was to determine the therapeutic potential of the pan-AKT inhibitor, AZD5363, in PTEN-deficient prostate cancer. Here we used a genetically engineered mouse (GEM) model of PTEN-deficient prostate cancer to evaluate the in vivo pharmacodynamic and antitumor activity of AZD5363 in castration-naïve and castration-resistant prostate cancer. An additional GEM model, based on the concomitant inactivation of PTEN and Trp53 (P53), was established as an aggressive model of advanced prostate cancer and was used to further evaluate clinically relevant endpoints after treatment with AZD5363. In vivo pharmacodynamic studies demonstrated that AZD5363 effectively inhibited downstream targets of AKT. AZD5363 monotherapy significantly reduced growth of tumors in castration-naïve and castration-resistant models of PTEN-deficient prostate cancer. More importantly, AZD5363 significantly delayed tumor growth and improved overall survival and progression-free survival in PTEN/P53 double knockout mice. Our findings demonstrate that AZD5363 is effective against GEM models of PTEN-deficient prostate cancer and provide lines of evidence to support further investigation into the development of treatment strategies targeting AKT for the treatment of PTEN-deficient prostate cancer.

Entrectinib is a potent inhibitor of Trk-driven neuroblastomas in a xenograft mouse model

Neuroblastoma (NB) is one of the most common and deadly childhood solid tumors. These tumors are characterized by clinical heterogeneity, from spontaneous regression to relentless progression, and the Trk family of neurotrophin receptors plays an important role in this heterogeneous behavior. We wanted to determine if entrectinib (RXDX-101, Ignyta, Inc.), an oral Pan-Trk, Alk and Ros1 inhibitor, was effective in our NB model. In vitro effects of entrectinib, either as a single agent or in combination with the chemotherapeutic agents Irinotecan (Irino) and Temozolomide (TMZ), were studied on an SH-SY5Y cell line stably transfected with TrkB. In vivo growth inhibition activity was studied in NB xenografts, again as a single agent or in combination with Irino-TMZ. Entrectinib significantly inhibited the growth of TrkB-expressing NB cells in vitro, and it significantly enhanced the growth inhibition of Irino-TMZ when used in combination. Single agent therapy resulted in significant tumor growth inhibition in animals treated with entrectinib compared to control animals [p < 0.0001 for event-free survival (EFS)]. Addition of entrectinib to Irino-TMZ also significantly improved the EFS of animals compared to vehicle or Irino-TMZ treated animals [p < 0.0001 for combination vs. control, p = 0.0012 for combination vs. Irino-TMZ]. We show that entrectinib inhibits growth of TrkB expressing NB cells in vitro and in vivo, and that it enhances the efficacy of conventional chemotherapy in in vivo models. Our data suggest that entrectinib is a potent Trk inhibitor and should be tested in clinical trials for NBs and other Trk-expressing tumors.

Preclinical mouse cancer models: a maze of opportunities and challenges

Significant advances have been made in developing novel therapeutics for cancer treatment, and targeted therapies have revolutionized the treatment of some cancers. Despite the promise, only about five percent of new cancer drugs are approved, and most fail due to lack of efficacy. The indication is that current preclinical methods are limited in predicting successful outcomes. Such failure exacts enormous cost, both financial and in the quality of human life. This Primer explores the current status, promise, and challenges of preclinical evaluation in advanced mouse cancer models and briefly addresses emerging models for early-stage preclinical development.

Correlative Studies in Clinical Trials: A Position Statement From the International Thyroid Oncology Group

OBJECTIVE

Patients with progressive thyroid cancer in distant metastatic sites represent a population with a need for new therapeutic options. Aspiring to improve the treatment of such patients, the objective of this position statement from the International Thyroid Oncology Group (ITOG) is to clarify the importance of incorporating high-quality correlative studies into clinical trials.

PARTICIPANTS

ITOG was formed to develop and support high-quality multicenter and multidisciplinary clinical trials for patients with aggressive forms of thyroid cancer. The Correlative Sciences Committee of the ITOG focuses on the quality and types of correlative studies included in ITOG-associated clinical trials.

EVIDENCE

This document represents expert consensus from ITOG regarding this issue based on extensive collective experience in clinical and translational trials informed by basic science.

CONSENSUS PROCESS

The Correlative Studies Committee identified an international writing group representative of diverse specialties, including basic sciences. Drafts were reviewed by all members of the writing group, the larger committee, and the ITOG board. After consideration of all comments by the writing group and modification of the document, the final document was then approved by the authors and the ITOG board.

CONCLUSIONS

High-quality correlative studies, which include variety in the types of correlates, should be intrinsic to the design of thyroid cancer clinical trials to offer the best opportunity for each study to advance treatment for patients with advanced and progressive thyroid cancer.

Combined HSP90 and kinase inhibitor therapy: Insights from The Cancer Genome Atlas

The merging of knowledge from genomics, cellular signal transduction and molecular evolution is producing new paradigms of cancer analysis. Protein kinases have long been understood to initiate and promote malignant cell growth and targeting kinases to fight cancer has been a major strategy within the pharmaceutical industry for over two decades. Despite the initial success of kinase inhibitors (KIs), the ability of cancer to evolve resistance and reprogram oncogenic signaling networks has reduced the efficacy of kinase targeting. The molecular chaperone HSP90 physically supports global kinase function while also acting as an evolutionary capacitor. The Cancer Genome Atlas (TCGA) has compiled a trove of data indicating that a large percentage of tumors overexpress or possess mutant kinases that depend on the HSP90 molecular chaperone complex. Moreover, the overexpression or mutation of parallel activators of kinase activity (PAKA) increases the number of components that promote malignancy and indirectly associate with HSP90. Therefore, targeting HSP90 is predicted to complement kinase inhibitors by inhibiting oncogenic reprogramming and cancer evolution. Based on this hypothesis, consideration should be given by both the research and clinical communities towards combining kinase inhibitors and HSP90 inhibitors (H90Ins) in combating cancer. The purpose of this perspective is to reflect on the current understanding of HSP90 and kinase biology as well as promote the exploration of potential synergistic molecular therapy combinations through the utilization of The Cancer Genome Atlas.

An Efficient Synthesis of Ceritinib (LDK378) Using a Sandmeyer Reaction

A convenient route for the synthesis of Novartis's second-generation anaplastic lymphoma kinase inhibitor Ceritinib (LDK378) involving starting materials that are commercially available has been achieved. The procedure employed mild reaction conditions and avoided the use of expensive reagents compared to the original synthetic route reported by Novartis. More importantly, gram scale synthesis was accomplished and this protocol could be valid in drug discovery synthesis.

Pulmonary epithelioid inflammatory myofibroblastic sarcoma with multiple bone metastases: case report and review of literature

Epithelioid inflammatory myofibroblastic sarcoma (EIMS) is a rare variant of inflammatory myofibroblastic tumor with distinctive morphological features and malignant clinical behavior. Only a few such cases have been described in the literature. We report here a case of unusual pulmonary EIMS with multiple bone metastases. A 21-year-old Chinese male patient presented with complaints of general fatigue and rapid weight loss, and a huge tumor arising in the left lower lobe of lung was detected by chest computed tomography. The mass of lung was totally resected. Microscopically, the tumor cells were rounded and epithelioid in shape. Myxoid stroma and inflammatory infiltration was also present. The tumor cells were immunopositive to anaplastic lymphoma kinase (ALK) in smooth cytoplasmic pattern. Fluorescence in situ hybridization (FISH) assay revealed the presence of rearrangement of ALK gene. Three months after lung surgery, there were multiple bone metastases and intraspinal mass found by positron emission tomography. The second surgical treatment was performed to remove the intraspinal lesion. The histological and immunohistochemical features of intraspinal mass were similar to those of pulmonary tumor. The diagnosis of pulmonary EIMS with multiple bone metastases was made. To the best of our knowledge, it may be the first case of an EIMS arising in lung. Awareness of EIMS in respiratory tract and its distinctive features is important for pathologists to avoid a diagnostic pitfall caused by histologic similarities to other ALK-positive tumors. ALK inhibitor is a promising treatment for this aggressive tumor regardless of its potential acquired resistance.

A first-in-human phase I, dose-escalation, multicentre study of HSP990 administered orally in adult patients with advanced solid malignancies

BACKGROUND

Heat-shock protein 990 (HSP990) is a potent and selective synthetic small-molecule HSP90 inhibitor. The primary objectives of this phase I first-in-human study were to determine dose-limiting toxicities (DLTs), maximum-tolerated dose (MTD) and recommended phase II dose (RP2D). Secondary objectives included characterisation of the safety profile, pharmacokinetics (PKs) and pharmacodynamics (PDs).

METHODS

Heat-shock protein 990 was administered orally once or two times weekly on a 28-day cycle schedule in patients with advanced solid tumours. Dose escalation was guided by a Bayesian logistic regression model with overdose control.

RESULTS

A total of 64 patients were enrolled. Fifty-three patients received HSP990 once weekly at 2.5, 5, 10, 20, 30, 50 or 60 mg, whereas 11 patients received HSP990 two times weekly at 25 mg. Median duration of exposure was 8 weeks (range 1-116 weeks) and 12 patients remained on treatment for >16 weeks. Dose-limiting toxicities occurred in seven patients and included diarrhoea, QTc prolongation, ALT/AST elevations and central neurological toxicities. The most common drug-related adverse events were diarrhoea, fatigue and decreased appetite. Further dose escalation beyond 60 mg once weekly was not possible owing to neurological toxicity. Rapid absorption, no drug accumulation and large interpatient variability in PK exposures were observed. No objective responses were seen; 25 patients had a best overall response of stable disease.

CONCLUSIONS

Heat-shock protein 990 is relatively well tolerated, with neurological toxicity being the most relevant DLT. The single agent MTD/RP2D of HSP990 was declared at 50 mg once weekly.

Hsp90 inhibitor as a sensitizer of cancer cells to different therapies (review)

Hsp90 is a molecular chaperone that maintains the structural and functional integrity of various client proteins involved in signaling and many other functions of cancer cells. The natural inhibitors, ansamycins influence the Hsp90 chaperone function by preventing its binding to client proteins and resulting in their proteasomal degradation. N- and C-terminal inhibitors of Hsp90 and their analogues are widely tested as potential anticancer agents in vitro, in vivo as well as in clinical trials. It seems that Hsp90 competitive inhibitors target different tumor types at nanomolar concentrations and might have therapeutic benefit. On the contrary, some Hsp90 inhibitors increased toxicity and resistance of cancer cells induced by heat shock response, and through the interaction of survival signals, that occured as side effects of treatments, could be very effectively limited via combination of therapies. The aim of our review was to collect the data from experimental and clinical trials where Hsp90 inhibitor was combined with other therapies in order to prevent resistance as well as to potentiate the cytotoxic and/or antiproliferative effects.

A co-clinical platform to accelerate cancer treatment optimization

Sophistication in DNA and RNA sequencing technology is unraveling the tremendous genetic and molecular complexity of human cancer. However, the rate at which this knowledge is being translated into patient care is too slow. To this end, we have designed and implemented a new translational platform, 'The Co-Clinical Trial Project', where data obtained in genetically engineered mouse models (GEMMs) of human cancer treated with protocols identical to those of ongoing clinical trials or with therapies already established in patients serve to rapidly: (i) stratify patients in terms of response and resistance on the basis of genetic and molecular criteria; (ii) identify mechanisms responsible for tumor resistance; and (iii) evaluate the effectiveness of drug combinations to overcome such resistance based on mechanistic understanding.

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26–27, 2013, entitled “Correlating Imaging Phenotypes with Genomics Signatures Research” and “Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems.” The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Modeling lung cancer evolution and preclinical response by orthotopic mouse allografts

Cancer evolution is a process that is still poorly understood because of the lack of versatile in vivo longitudinal studies. By generating murine non-small cell lung cancer (NSCLC) orthoallobanks and paired primary cell lines, we provide a detailed description of an in vivo, time-dependent cancer malignization process. We identify the acquisition of metastatic dissemination potential, the selection of co-driver mutations, and the appearance of naturally occurring intratumor heterogeneity, thus recapitulating the stochastic nature of human cancer development. This approach combines the robustness of genetically engineered cancer models with the flexibility of allograft methodology. We have applied this tool for the preclinical evaluation of therapeutic approaches. This system can be implemented to improve the design of future treatments for patients with NSCLC.

Non-small-cell lung cancers: a heterogeneous set of diseases

Non-small-cell lung cancers (NSCLCs), the most common lung cancers, are known to have diverse pathological features. During the past decade, in-depth analyses of lung cancer genomes and signalling pathways have further defined NSCLCs as a group of distinct diseases with genetic and cellular heterogeneity. Consequently, an impressive list of potential therapeutic targets was unveiled, drastically altering the clinical evaluation and treatment of patients. Many targeted therapies have been developed with compelling clinical proofs of concept; however, treatment responses are typically short-lived. Further studies of the tumour microenvironment have uncovered new possible avenues to control this deadly disease, including immunotherapy.