Biomarker-guided targeted and immunotherapies in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a lethal thoracic malignancy whose incidence is still increasing worldwide. MPM is characterized by frequent inactivation of tumor-suppressor genes (TSGs), e.g., the homozygous deletion of CDKN2A/2B and various genetic alterations that inactivate BAP1, NF2, LATS1/2, and TP53. The leading cause for the poor prognosis of patients with MPM is the lack of effective treatment options, with conventional chemotherapy being the standard of care in the clinic, which has remained unchanged for almost 20 years. Precision oncology, a burgeoning effort to provide precise cancer treatment tailored to unique molecular changes in individual patients, has made tremendous progress in the last decade in several cancers, but not in MPM. Recent studies indicate a high degree of tumor heterogeneity in MPM and the importance to optimize histological and molecular classifications for improved treatment. In this review, we provide an up-to-date overview of recent advances in MPM by focusing on new stratifications of tumor subgroups, specific vulnerabilities associated with functional loss of TSGs and other biomarkers, and potential clinical implications. The molecularly based subdivisions not only deepen our understanding of MPM pathobiology, but more importantly, they may raise unprecedented new hopes for personalized treatment of MPM patients with biomarker-guided targeted and immunotherapies.

Pharmacotranscriptomic Analysis Reveals Novel Drugs and Gene Networks Regulating Ferroptosis in Cancer

(1) Background: Ferroptosis is an apoptosis-independent cell death program implicated in many diseases including cancer. Emerging evidence suggests ferroptosis as a promising avenue for cancer therapy, but the paucity of mechanistic understanding of ferroptosis regulation and lack of biomarkers for sensitivity to ferroptosis inducers have significantly hampered the utility of ferroptosis-based therapy. (2) Methods: We performed integrated dataset analysis by correlating the sensitivity of small-molecule compounds (n = 481) against the transcriptomes of solid cancer cell lines (n = 659) to identify drug candidates with the potential to induce ferroptosis. Generalizable gene signatures of ferroptosis sensitivity and resistance are defined by interrogating drug effects of ferroptosis inducers (n = 7) with transcriptomic data of pan-solid cancer cells. (3) Results: We report, for the first time, the comprehensive identification of drug compounds that induce ferroptosis and the delineation of generalizable gene signatures of pro- and anti-ferroptosis in pan-cancer. We further reveal that small cell lung cancer (SCLC) and isocitrate dehydrogenase (IDH1/2)-mutant brain tumors show enrichment of pro-ferroptosis gene signature, suggesting a unique vulnerability of SCLC and IDH-mutant tumors to ferroptosis inducers. Finally, we demonstrate that targeting class I histone deacetylase (HDAC) significantly enhances ferroptotic cell death caused by Erastin, an ferroptosis inducer, in lung cancer cells, revealing a previously underappreciated role for HDAC in ferroptosis regulation. (4) Conclusions: Our work reveals novel drug compounds and gene networks that regulate ferroptosis in cancer, which sheds light on the mechanisms of ferroptosis and may facilitate biomarker-guided stratification for ferroptosis-based therapy.

Why Great Mitotic Inhibitors Make Poor Cancer Drugs

Chemotherapy is central to oncology, perceived to operate only on prolific cancerous tissue. Yet, many non-neoplastic tissues are more prolific compared with typical tumors. Chemotherapies achieve sufficient therapeutic windows to exert antineoplastic activity because they are prodrugs that are bioactivated in cancer-specific environments. The advent of precision medicine has obscured this concept, favoring the development of high-potency kinase inhibitors. Inhibitors of essential mitotic kinases exemplify this paradigm shift, but intolerable on-target toxicities in more prolific normal tissues have led to repeated failures in the clinic. Proliferation rates alone cannot be used to achieve cancer specificity. Here, we discuss integrating the cancer specificity of prodrugs from classical chemotherapeutics and the potency of mitotic kinase inhibitors to generate a class of high-precision cancer therapeutics.

Treatment strategy for papillary renal cell carcinoma type 2: a case series of seven patients treated based on next generation sequencing data

Background

Papillary renal cell carcinoma type 2 (PRCC2) is refractory to systemic treatment and has a dismal prognosis. Previous studies showed that genetic alterations in PRCC2 were heterogeneous regardless of germline or somatic mutations. In this study, we aimed to perform precision treatment of PRCC2 based on genetic information.

Methods

We performed exome and genome sequencing of tumor tissues and matched normal samples. Based on sequencing data, we treated patients with metastatic PRCC2 using precision oncology.

Results

Four patients underwent curative surgery of PRCC2 and three patients had metastatic PRCC2. All PRCC2 heterogeneously harbored own driver mutations. Two out of the three patients with metastatic disease had fumarate hydratase (FH) germline mutations. One patient with a germline FH mutation was diagnosed with hereditary leiomyomatosis RCC. He was treated with bevacizumab and erlotinib combination and showed a durable response. The other metastatic PRCC2 patient harboring a germline FH mutation had an additional somatic FH mutation and was durably controlled with pazopanib. Other metastatic PRCC2 patient with somatic PBRM1 and SETD2 mutations had over 5 years of overall survival with axitinib treatment.

Conclusions

We performed precision systemic treatment based on genetic information. Genome sequencing could help identify candidates for targeted therapy in PRCC2, a genetically heterogeneous disease.

Molecular Profiling of Malignant Pleural Effusions with Next Generation Sequencing (NGS): Evidence that Supports Its Role in Cancer Management

Malignant pleural effusions (MPEs) often develop in advanced cancer patients and confer significant morbidity and mortality. In this review, we evaluated whether molecular profiling of MPEs with next generation sequencing (NGS) could have a role in cancer management, focusing on lung cancer. We reviewed and compared the diagnostic performance of pleural fluid liquid biopsy with other types of samples. When applied in MPEs, NGS may have comparable performance with corresponding tissue biopsies, yield higher DNA amount, and detect more genetic aberrations than blood-derived liquid biopsies. NGS in MPEs may also be preferable to plasma liquid biopsy in advanced cancer patients with a MPE and a paucicellular or it could be difficult to obtain tissue/fine-needle aspiration biopsy. Of interest, post-centrifuge supernatant NGS may exhibit superior results compared to cell pellet, cell block or other materials. NGS in MPEs can also guide clinicians in tailoring established therapies and identifying therapy resistance. Evidence is still premature regarding the role of NGS in MPEs from patients with cancers other than lung. We concluded that MPE processing could provide useful prognostic and theranostic information, besides its diagnostic role.

Trametinib Induces the Stabilization of a Dual GNAQ p.Gly48Leu- and FGFR4 p.Cys172Gly-Mutated Uveal Melanoma. The Role of Molecular Modelling in Personalized Oncology

We report a case of an uveal melanoma patient with GNAQ p.Gly48Leu who responded to MEK inhibition. At the time of the molecular analysis, the pathogenicity of the mutation was unknown. A tridimensional structural analysis showed that Gαq can adopt active and inactive conformations that lead to substantial changes, involving three important switch regions. Our molecular modelling study predicted that GNAQ p.Gly48Leu introduces new favorable interactions in its active conformation, whereas little or no impact is expected in its inactive form. This strongly suggests that GNAQ p.Gly48Leu is a possible tumor-activating driver mutation, consequently triggering the MEK pathway. In addition, we also found an FGFR4 p.Cys172Gly mutation, which was predicted by molecular modelling analysis to lead to a gain of function by impacting the Ig-like domain 2 folding, which is involved in FGF binding and increases the stability of the homodimer. Based on these analyses, the patient received the MEK inhibitor trametinib with a lasting clinical benefit. This work highlights the importance of molecular modelling for personalized oncology.

Integrating proteomics into precision oncology

DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole-exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology.

Building towards Precision Oncology for Pancreatic Cancer: Real-World Challenges and Opportunities

The advent of next-generation sequencing (NGS) has provided unprecedented insight into the molecular complexity of pancreatic ductal adenocarcinoma (PDAC). This has led to the emergence of biomarker-driven treatment paradigms that challenge empiric treatment approaches. However, the growth of sequencing technologies is outpacing the development of the infrastructure required to implement precision oncology as routine clinical practice. Addressing these logistical barriers is imperative to maximize the clinical impact of molecular profiling initiatives. In this review, we examine the evolution of precision oncology in PDAC, spanning from germline testing for cancer susceptibility genes to multi-omic tumor profiling. Furthermore, we highlight real-world challenges to delivering precision oncology for PDAC, and propose strategies to improve the generation, interpretation, and clinical translation of molecular profiling data.

The Pan-Omics Landscape of Renal Cell Carcinoma and Its Implication on Future Clinical Practice

Renal cell carcinoma has traditionally been classified based on histological features. Contemporary studies have identified genomic, transcriptomic, epigenomic, and metabolomic signatures that correspond to or even transcend histological subtypes. Much remains to be learned about improving the algorithm of pan-omics integration for precision oncology, which will not only advance our understanding of RCC pathobiology and treatment response but also result in novel therapeutic opportunities. Accordingly, this review focuses on recent RCC multi-omics literature. Encouragingly, a few reports on omics integration into routinely employed prognostic risk models have shown early promise that could lay the foundation for future development of precision kidney cancer therapies. Hence, this article serves as a primer on what we have learned and how we might better realize the clinical potential of the burgeoning pan-omics data.

FGFR inhibitors in cholangiocarcinoma: what's now and what's next?

Patients with intrahepatic cholangiocarcinoma (iCCA) face a highly dismal prognosis, due to late stage diagnosis, the relative chemoresistance of the disease, and an overall limited portfolio of established therapeutic concepts. In recent years, a number of next generation sequencing studies have provided detailed information on the molecular landscape of biliary malignancies, and have laid the groundwork for the evaluation of novel, targeted therapeutic opportunities. Although nearly 40% of patients harbor genetic alterations for which targeted options exist, rapid translation into clinical trials is hampered by the overall low patient numbers. One of the most frequent genetic events in patients with iCCAs are fusions that involve the fibroblast growth factor receptor 2 (FGFR2). Impressive results from pivotal phase II studies in pre-treated patients have confirmed that FGFR-inhibitors are a promising therapeutic option for this genetic subgroup, and the rapid pace with which these inhibitors are being clinically developed is clearly justified by the imminent benefit for the patients. However, the success of these agents should not blind us to key challenges that need to be addressed to optimize FGFR-directed therapies in the future. A better understanding of mechanisms that convey primary and secondary resistance will be crucial to improve up-front patient stratification, to prolong the duration of response, and to implement reasonable co-treatment approaches. In this review, we provide background information on the pathobiology of oncogenic FGFR fusions and selected genetic testing strategies, summarize the latest clinical data, and discuss future directions of FGFR-directed therapies in patients with iCCA.

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.

The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database

The Veterans Affairs Precision Oncology Data Repository (VA-PODR) is a large, nationwide repository of de-identified data on patients diagnosed with cancer at the Department of Veterans Affairs (VA). Data include longitudinal clinical data from the VA's nationwide electronic health record system and the VA Central Cancer Registry, targeted tumor sequencing data, and medical imaging data including computed tomography (CT) scans and pathology slides. A subset of the repository is available at the Genomic Data Commons (GDC) and The Cancer Imaging Archive (TCIA), and the full repository is available through the Veterans Precision Oncology Data Commons (VPODC). By releasing this de-identified dataset, we aim to advance Veterans' health care through enabling translational research on the Veteran population by a wide variety of researchers.

Genetic and genomic alterations differentially dictate low-grade glioma growth through cancer stem cell-specific chemokine recruitment of T cells and microglia

BACKGROUND

One of the clinical hallmarks of low-grade gliomas (LGGs) arising in children with the neurofibromatosis type 1 (NF1) cancer predisposition syndrome is significant clinical variability with respect to tumor growth, associated neurologic deficits, and response to therapy. Numerous factors could contribute to this clinical heterogeneity, including the tumor cell of origin, the specific germline NF1 gene mutation, and the coexistence of additional genomic alterations. Since human specimens are rarely acquired, and have proven difficult to maintain in vitro or as xenografts in vivo, we have developed a series of Nf1 mutant optic glioma mouse strains representing each of these contributing factors.

METHODS

Optic glioma stem cells (o-GSCs) were generated from this collection of Nf1 genetically engineered mice, and analyzed for their intrinsic growth properties, as well as the production of chemokines that could differentially attract T cells and microglia.

RESULTS

The observed differences in Nf1 optic glioma growth are not the result of cell autonomous growth properties of o-GSCs, but rather the unique patterns of o-GSC chemokine expression, which differentially attract T cells and microglia. This immune profile collectively dictates the levels of chemokine C-C ligand 5 (Ccl5) expression, the key stromal factor that drives murine Nf1 optic glioma growth.

CONCLUSIONS

These findings reveal that genetic and genomic alterations create murine LGG biological heterogeneity through the differential recruitment of T cells and microglia by o-GSC-produced chemokines, which ultimately determine the expression of stromal factors that drive tumor growth.

Organoid models of glioblastoma: advances, applications and challenges

The high mortality and poor clinical prognosis of glioblastoma multiforme (GBM) are concerns for many GBM patients as well as clinicians and researchers. The lack of a preclinical model that can easily be established and accurately recapitulate tumour biology and the tumour microenvironment further complicates GBM research and its clinical translation. GBM organoids (GBOs) are promising high-fidelity models that can be applied to model the disease, develop drugs, establish a living biobank, mimic therapeutic responses and explore personalized therapy. However, GBO models face some challenges, including deficient immune responses, absent vascular system and controversial reliability. In recent years, considerable progress has been achieved in the improvement of brain tumour organoid models and research based on such models. In addition to the traditional cultivation method, these models can be cultivated via genetic engineering and co-culture of cerebral organoids and GBM. In this review, we summarize the applications of GBM organoids and related advances and provide our opinions on associated limitations and challenges.

Tumor organoids to study gastroesophageal cancer: a primer

Gastroesophageal cancers are leading causes of cancer death. Our attempts at adopting molecularly based treatment approaches have been slow and ineffective even though we begin to identify specific targetable gene mutations and pathways. It is clear that we should no longer treat all gastroesophageal cancers as a homogeneous disease, which is what we do when we use non-specific chemotherapy. However, we currently cannot monitor successful gene/pathway targeting, nor understand how/when tumors develop resistance, nor predict which patients will derive maximal benefit. To improve outcomes, we must precisely detail the heterogeneity of these tumors to then individualize cancer therapy as well as develop novel avenues to study and predict treatment effects in individual patients. To this end, patient-derived organoids, in which tumor cells from individual patients are grown in a Petri dish, are a new versatile system that allows for timely expandability, detailed molecular characterization, and genetic manipulation with the promise of enabling predictive assessment of treatment response. In this review, we will explore the development and basic techniques for organoid generation, and discuss the current and potential future applications of this exciting technology to study the basic science of carcinogenesis and to predict/guide cancer patient care in the clinics.

The role of microRNAs in gliomas - Therapeutic implications

Background Malignant gliomas constitute a complex disease phenotype that demands optimum decisionmaking. Despite being the most common type of primary brain tumors, gliomas are highly heterogeneous when their pathophysiology and response to treatment are considered. Such inter-individual variability also renders differential and early diagnosis extremely difficult. Recent evidence highlight that the gene-environment interplay becomes of fundamental importance in oncogenesis and progression of gliomas.

OBJECTIVE

To unmask key features of the gliomas disease phenotype and map the inter-individual variability of patients, we explore genotype-to-phenotype associations. Emphasis is put on microRNAs as they regulate gene expression, have been implicated in the pathogenesis of gliomas and may serve as theranostics, empowering non-invasive strategies (circulating free or in exosomes).

METHOD

We mined text and omic datasets (as of 2019) and conducted a mixed-method content analysis. A novel framework was developed to meet the aims of our analysis, interrogating data in terms of content and context. We relied on literature data from PubMed/Medline and Scopus, as they are considered the largest abstract and citation databases of peer-reviewed literature. To avoid selection biases, both publicly available and private texts have been assessed. Both percent agreement and Cohen's kappa statistic have been calculated to avoid biases by SAS macro MAGREE with multicategorical ratings.

RESULTS

Gliomas serve as a paradigm for multifaceted datasets, despite data sparsity and scarcity. miRNAs and miRNAbased therapeutics are ready for prime time. Exosomal miRNAs empower non-invasive strategies, surpassing circulating free miRNAs, when accuracy and precision are considered.

CONCLUSION

miRNAs holds promise as theranostics.

From the Broad Phase II Trial to Precision Oncology: A Perspective on the Origins of Basket and Umbrella Clinical Trial Designs in Cancer Drug Development

Oncologic phase II trials that evaluate the activity of new therapeutic agents have evolved dramatically over the past 50 years. The standard approach beginning in the late 1960s focused on individual studies that evaluated new anticancer agents against a wide range of both solid and hematopoietic malignancies often in a single "broad phase II trial" that included hundreds of patients; such studies efficiently established the landscape for subsequent development of a specific drug with respect to likely disease focus, toxicity, dose, and schedule. In the 1980s and 1990s, emphasis on histological context drove an explosion in the number of individual phase II trials conducted; despite this increase in trial activity, investigations based on histology per se failed to improve the success rate of new agents brought to the clinic. Over the past 20 years, evolution toward a molecular drug development paradigm has demonstrably improved our ability to select patients more likely to benefit from systemic treatment; simultaneously, technological advances have permitted initial attempts at the rapid assignment of therapy based on predefined molecular characteristics of tumor or germline in broad-based master protocols that are inclusive of many diseases and molecularly characterized disease subsets, akin to but much more sophisticated scientifically than the broad phase II platforms of the past.

Clinical Applications of Next-Generation Sequencing in Precision Oncology

The ability of next-generation sequencing (NGS) to comprehensively assess the molecular profile of a tumor specimen has transformed the clinical testing landscape in oncology. Accordingly, recent years have seen broad uptake of clinical NGS to inform cancer patient management. However, significant challenges remain. The annotation and clinical interpretation of variants identified by NGS tests often require rigorous review and may vary between laboratories. While a clearer regulatory path has emerged, reimbursement for NGS tests remains a subject of continuing debate. Basket clinical studies such as the National Cancer Institute Molecular Analysis of Therapy Choice are evaluating the degree to which matching of a targeted therapy to tumor molecular profile by NGS can be applied independently of tissue histology. Newer applications of NGS such as for circulating tumor DNA testing and to identify novel RNA fusion driver events continue to expand its clinical utility.

Molecular Profiling of Advanced Malignancies: A Community Oncology Network Experience and Review of Literature

Background: Many genomic alterations have been identified that are critical to the malignant phenotype. Some of these, termed “driver mutations,” are critical for tumor proliferation and progression. The landscape of targeted therapy has expanded as well. Next-generation sequencing (NGS) of tumors reveals cancer-related genomic alterations and provides therapeutic recommendations for specific targeted therapy. We analyzed our experience with FoundationOne, a validated NGS genomic profiling test, in a community oncology network.

Methods: NGS results from May 2014 to September 2016 from a community oncology network in Western Pennsylvania were analyzed. Medical records were reviewed for primary site, stage, biopsy site, time of testing, prior treatment, FDA-approved therapy in patient's and other tumor types and potential clinical trials based upon mutations detected. Two co-primary endpoints for this study were to determine the percentage of patients having mutations with a FDA-approved targeted agent and the percentage of patients in whom a treatment decision was made based on these NGS results.

Results: One Fifty-Seven NGS results were available for analysis. 82% patients had a mutation with a FDA-approved targeted agent available while 18% patients had no FDA-approved targeted agent for the mutation detected. Clinical trials were available for 93% cases. The NGS results were utilized in treatment decisions in 18% patients (n = 28) with, 7% (n = 11) initiating a targeted agent, 6% (n = 9) were on an appropriate targeted agent prior to testing and 5% (n = 8) being unable to start a targeted agent because of insurance denial, clinical deterioration or patient preference. 38% cases were tested early in the disease course (at diagnosis, during or shortly after first-line treatment) and 62% at progression.

Conclusions: NGS is a valuable tool to identify molecular targets for personalizing cancer care. From our experience, the actual number of patients starting a targeted agent based on NGS results is low but it provides substantial information in terms of providing additional treatment options, identifying resistance conferring mutations and facilitating clinical trial enrollment. Optimal time of testing, early or late in disease course, financial implications of testing and using targeted therapy and survival benefit of targeted therapy need further studies.

Possible role of circulating tumor cells in early detection of lung cancer

The prognosis of lung cancer varies highly depending on the disease stage at diagnosis, from a 5-year survival rate close to 90% in stage I, to 10% or less in stage IV disease. The enhancement of early diagnosis of this malignancy is mandatory to improve prognosis, because lung cancer patients stay long asymptomatic or few symptomatic after disease onset. Nowadays, liquid biopsy has emerged as a minimally-invasive tool to address the urgent need for real time monitoring, stratification, and personalized treatment of malignancies, including lung cancer. Liquid biopsy refers to a class of biomarkers, including circulating tumor cells (CTCs), cell-free circulating tumor DNA (ctDNA) and tumor-derived extracellular vesicles (tdEV). Since CTCs represent a crucial step in disease progression and metastasis, we reviewed here the scientific literature about the use of CTCs in early diagnosis of lung cancer; different techniques, and different strategies (e.g., source of analysis sample or high-risk groups of patients) were discussed showing the potential of implementing liquid biopsy in the clinical routine of non-metastatic lung cancer.

ExoBCD: a comprehensive database for exosomal biomarker discovery in breast cancer

Effective and safe implementation of precision oncology for breast cancer is a vital strategy to improve patient outcomes, which relies on the application of reliable biomarkers. As 'liquid biopsy' and novel resource for biomarkers, exosomes provide a promising avenue for the diagnosis and treatment of breast cancer. Although several exosome-related databases have been developed, there is still lacking of an integrated database for exosome-based biomarker discovery. To this end, a comprehensive database ExoBCD (https://exobcd.liumwei.org) was constructed with the combination of robust analysis of four high-throughput datasets, transcriptome validation of 1191 TCGA cases and manual mining of 950 studies. In ExoBCD, approximately 20 900 annotation entries were integrated from 25 external sources and 306 exosomal molecules (49 potential biomarkers and 257 biologically interesting molecules). The latter could be divided into 3 molecule types, including 121 mRNAs, 172 miRNAs and 13 lncRNAs. Thus, the well-linked information about molecular characters, experimental biology, gene expression patterns, overall survival, functional evidence, tumour stage and clinical use were fully integrated. As a data-driven and literature-based paradigm proposed of biomarker discovery, this study also demonstrated the corroborative analysis and identified 36 promising molecules, as well as the most promising prognostic biomarkers, IGF1R and FRS2. Taken together, ExoBCD is the first well-corroborated knowledge base for exosomal studies of breast cancer. It not only lays a foundation for subsequent studies but also strengthens the studies of probing molecular mechanisms, discovering biomarkers and developing meaningful clinical use.

Update on Circulating Tumor Cells in Genitourinary Tumors with Focus on Prostate Cancer

Current developments in the treatment of genitourinary tumors underline the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting. The detection of circulating tumor cells (CTCs) has become one of the most exciting and important new approaches to identifying biomarkers at different stages of disease in a non-invasive way. Potential applications of CTCs include monitoring treatment efficacy and early detection of progression, selecting tailored therapies, as well as saving treatment costs. However, despite the promising implementation of CTCs in a clinical scenario, the isolation and characterization of these cells for molecular studies remain expensive with contemporary platforms, and significant technical challenges still need to be overcome. This updated, critical review focuses on the state of CTCs in patients with genitourinary tumor with focus on prostate cancer, discussing technical issues, main clinical results and hypothesizing potential future perspectives in clinical scenarios.

The Potential of Tumor Debulking to Support Molecular Targeted Therapies

Tumors may consist of billions of cells, which in malignant cases disseminate and form distant metastases. The large number of tumor cells formed by the high number of cell divisions during tumor progression creates a heterogeneous set of genetically diverse tumor cell clones. For cancer therapy this poses unique challenges, as distinct clones have to be targeted in different tissue locations. Recent research has led to the development of specific inhibitors of defined targets in cellular signaling cascades which promise more effective and more tumor-specific therapy approaches. Many of these molecular targeted therapy (MTT) compounds have already been translated into clinics or are currently being tested in clinical studies. However, the outgrowth of tumor cell clones resistant to such inhibitors is a drawback that affects specific inhibitors in a similar way as classical cytotoxic chemotherapeutics, because additionally acquired genetic alterations can enable tumor cells to circumvent the particular regulators of cellular signaling being targeted. Thus, it might be desirable to reduce genetic heterogeneity prior to molecular targeting, which could reduce the statistical chance of tumor relapse initiated by resistant clones. One way to achieve this is employing unspecific methods to remove as much tumor material as possible before MTT, e.g., by tumor debulking (TD). Currently, this is successfully applied in the clinical treatment of ovarian cancer. We believe that TD followed by treatment with a combination of molecular targeted drugs, optimally guided by biomarkers, might advance survival of patients suffering from various cancer types.