Genetic heterogeneity and cancer drug resistance

Integrated analysis profiles of long non-coding RNAs reveal potential biomarkers of drug resistance in lung cancer

Lung cancer is one of the leading causes of cancer-related death. Resistance to chemotherapy and molecularly targeted therapies is a major problem that can contribute substantially to high mortality. The roles of long non-coding RNAs (lncRNAs) in drug resistance of lung cancer are insufficiently understood. Here, we identified a distinct drug resistance-related transcriptional signature and constructed a functional lncRNA-mRNA co-expression network. We found that 34 lncRNAs and 103 mRNAs have differential expression in drug resistance of lung cancer, in which 10 lncRNAs were down regulated and 24 up regulated; 49 mRNAs were down regulated and 54 up regulated. LncRNAs-mRNAs expression network analysis revealed a role for lncRNAs in modulating cancer-related pathways. We also found that two pair lncRNAs and their subnetworks were highly related to drug resistance. NR_028502.1/NR_028505.1 were found differentially co-expressed with nine mRNAs, and highly correlated with better clinical outcome. NR_030725.1/NR_030726.1 co-expressed with eleven mRNAs, and were associated with poor survival in patients with lung cancer. Our work comprehensively identified expression signature of resistance-associated lncRNAs and their inter-regulated mRNAs in lung cancer.

Local co-administration of gene-silencing RNA and drugs in cancer therapy: State-of-the art and therapeutic potential

Gene-silencing miRNA and siRNA are emerging as attractive therapeutics with potential to suppress any genes, which could be especially useful in combination cancer therapy to overcome multidrug resistant (MDR) cancer. Nanomedicine aims to advance cancer treatment through functional nanocarriers that delivers one or more therapeutics to cancer tissue and cells with minimal off-target effects and suitable release kinetics and dosages. Although much effort has gone into developing circulating nanocarriers with targeting functionality for systemic administration, another alternative and straightforward approach is to utilize formulations to be administered directly to the site of action, such as pulmonary and intratumoral delivery. The combination of gene-silencing RNA with drugs in nanocarriers for localized delivery is emerging with promising results. In this review, the current progress and strategies for local co-administration of RNA and drug for synergistic effects and future potential in cancer treatment are presented and discussed. Key advances in RNA-drug anticancer synergy and localized delivery systems were combined with a review of the available literature on local co-administration of RNA and drug for cancer treatment. It is concluded that advanced delivery systems for local administration of gene-silencing RNA and drug hold potential in treatment of cancer, depending on indication. In particular, there are promising developments using pulmonary delivery and intratumoral delivery in murine models, but further research should be conducted on other local administration strategies, designs that achieve effective intracellular delivery and maximize synergy and feasibility for clinical use.

The Cellular Origin and Evolution of Breast Cancer

In this review, we will discuss how the cell of origin may modulate breast cancer intratumoral heterogeneity (ITH) as well as the role of ITH in the evolution of cancer. The clonal evolution and the cancer stem cell (CSC) models, as well as a model that integrates clonal evolution with a CSC hierarchy, have all been proposed to explain the development of ITH. The extent of ITH correlates with clinical outcome and reflects the cellular complexity and dynamics within a tumor. A unique subtype of breast cancer, the claudin-low subtype that is highly resistant to chemotherapy and most closely resembles mammary epithelial stem cells, will be discussed. Furthermore, we will review how the interactions among various tumor cells, some with distinct mutations, may impact breast cancer treatment. Finally, novel technologies that may help advance our understanding of ITH and lead to improvements in the design of new treatments also will be discussed.

High-grade serous ovarian cancer: the clone wars

BACKGROUND

The last 5 years' studies using next-generation sequencing provided evidences that many types of solid tumors present spatial and temporal genetic heterogeneity and are composed of multiple populations of genetically distinct subclones that evolve over time following a pattern of branched evolution. The evolutionary nature of cancer has been proposed as the major contributor to drug resistance and treatment failure. In this review, we present the current state of knowledge about the clonal evolution of high-grade serous ovarian cancer and discuss the challenge that clonal evolution poses for efforts to achieve an optimal cancer control.

METHODS

A systemic search of peer-reviewed articles published between August 2007 and October 2016 was performed using PUBMED and Google Scholar database.

RESULTS AND CONCLUSIONS

Recent studies using next-generation sequencing have allowed us to look inside the evolutionary nature of high-grade serous ovarian cancer, which in the light of current evidence can explain the relapsing course of the disease frequently observed in the clinical practice. Since only minimal improvement in the survival of patients treated with standard therapy has been observed in the last decade, novel molecular targeted therapies are of great interest in high-grade serous ovarian cancer. However, both spatial and temporal intratumoral genetic heterogeneity is a major challenge for personalized medicine, and greater knowledge of the molecular rules that drive tumor evolution through space and time is required to achieve a long-term clinical benefit from personalized therapy.

Dual Inhibition of PDK1 and Aurora Kinase A: An Effective Strategy to Induce Differentiation and Apoptosis of Human Glioblastoma Multiforme Stem Cells

The poor prognosis of glioblastoma multiforme (GBM) is mainly attributed to drug resistance mechanisms and to the existence of a subpopulation of glioma stem cells (GSCs). Multitarget compounds able to both affect different deregulated pathways and the GSC subpopulation could escape tumor resistance and, most importantly, eradicate the stem cell reservoir. In this respect, the simultaneous inhibition of phosphoinositide-dependent kinase-1 (PDK1) and aurora kinase A (AurA), each one playing a pivotal role in cellular survival/migration/differentiation, could represent an innovative strategy to overcome GBM resistance and recurrence. Herein, the cross-talk between these pathways was investigated, using the single-target reference compounds MP7 (PDK1 inhibitor) and Alisertib (AurA inhibitor). Furthermore, a new ligand, SA16, was identified for its ability to inhibit the PDK1 and the AurA pathways at once, thus proving to be a useful tool for the simultaneous inhibition of the two kinases. SA16 blocked GBM cell proliferation, reduced tumor invasiveness, and triggered cellular apoptosis. Most importantly, the AurA/PDK1 blocker showed an increased efficacy against GSCs, inducing their differentiation and apoptosis. To the best of our knowledge, this is the first report on combined targeting of PDK1 and AurA. This drug represents an attractive multitarget lead scaffold for the development of new potential treatments for GBM and GSCs.

Discovery and preclinical evaluation of 7-benzyl-N-(substituted)-pyrrolo[3,2-d]pyrimidin-4-amines as single agents with microtubule targeting effects along with triple-acting angiokinase inhibition as antitumor agents

The utility of cytostatic antiangiogenic agents (AA) in cancer chemotherapy lies in their combination with cytotoxic chemotherapeutic agents. Clinical combinations of AA with microtubule targeting agents (MTAs) have been particularly successful. The discovery, synthesis and biological evaluations of a series of 7-benzyl-N-substituted-pyrrolo[3,2-d]pyrimidin-4-amines are reported. Novel compounds which inhibit proangiogenic receptor tyrosine kinases (RTKs) including vascular endothelial growth factor receptor-2 (VEGFR-2), platelet-derived growth factor receptor-β (PDGFR-β) and epidermal growth factor receptor (EGFR), along with microtubule targeting in single molecules are described. These compounds also inhibited blood vessel formation in the chicken chorioallantoic membrane (CAM) assay, and some potently inhibited tubulin assembly (with activity comparable to that of combretastatin A-4 (CA)). In addition, some of the analogs circumvent the most clinically relevant tumor resistance mechanisms (P-glycoprotein and β-III tubulin expression) to microtubule targeting agents (MTA). These MTAs bind at the colchicine site on tubulin. Two analogs displayed two to three digit nanomolar GI50 values across the entire NCI 60 tumor cell panel and one of these, compound 7, freely water soluble as its HCl salt, afforded excellent in vivo antitumor activity against an orthotopic triple negative 4T1 breast cancer model and was superior to doxorubicin.

Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity

One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research.

Co-delivery of doxorubicin and methotrexate by dendritic chitosan-g-mPEG as a magnetic nanocarrier for multi-drug delivery in combination chemotherapy

Nanoparticulate drug delivery systems have the potential to improve the therapeutic efficacy of anticancer agents, and combination therapy is a promising strategy for clinical cancer treatment with synergistic effects.

Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis

Tumour heterogeneity refers to the fact that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity), and it is caused by genetic and non-genetic factors. The heterogeneity of cancer cells introduces significant challenges in using molecular prognostic markers as well as for classifying patients that might benefit from specific therapies. Thus, research efforts for characterizing heterogeneity would be useful for a better understanding of the causes and progression of disease. It has been suggested that the study of heterogeneity within Circulating Tumour Cells (CTCs) could also reflect the full spectrum of mutations of the disease more accurately than a single biopsy of a primary or metastatic tumour. In previous years, many high throughput methodologies have raised for the study of heterogeneity at different levels (i.e., RNA, DNA, protein and epigenetic events). The aim of the current review is to stress clinical implications of tumour heterogeneity, as well as current available methodologies for their study, paying specific attention to those able to assess heterogeneity at the single cell level.

Somatic mutation detection using various targeted detection assays in paired samples of circulating tumor DNA, primary tumor and metastases from patients undergoing resection of colorectal liver metastases

Assessing circulating tumor DNA (ctDNA) is a promising method to evaluate somatic mutations from solid tumors in a minimally-invasive way. In a group of twelve metastatic colorectal cancer (mCRC) patients undergoing liver metastasectomy, from each patient DNA from cell-free DNA (cfDNA), the primary tumor, metastatic liver tissue, normal tumor-adjacent colon or liver tissue, and whole blood were obtained. Investigated was the feasibility of a targeted NGS approach to identify somatic mutations in ctDNA. This targeted NGS approach was also compared with NGS preceded by mutant allele enrichment using synchronous coefficient of drag alteration technology embodied in the OnTarget assay, and for selected mutations with digital PCR (dPCR). All tissue and cfDNA samples underwent IonPGM sequencing for a CRC-specific 21-gene panel, which was analyzed using a standard and a modified calling pipeline. In addition, cfDNA, whole blood and normal tissue DNA were analyzed with the OnTarget assay and with dPCR for specific mutations in cfDNA as detected in the corresponding primary and/or metastatic tumor tissue. NGS with modified calling was superior to standard calling and detected ctDNA in the cfDNA of 10 patients harboring mutations in APC, ATM, CREBBP, FBXW7, KRAS, KMT2D, PIK3CA and TP53. Using this approach, variant allele frequencies in plasma ranged predominantly from 1 to 10%, resulting in limited concordance between ctDNA and the primary tumor (39%) and the metastases (55%). Concordance between ctDNA and tissue markedly improved when ctDNA was evaluated for KRAS, PIK3CA and TP53 mutations by the OnTarget assay (80%) and digital PCR (93%). Additionally, using these techniques mutations were observed in tumor-adjacent tissue with normal morphology in the majority of patients, which were not observed in whole blood. In conclusion, in these mCRC patients with oligometastatic disease NGS on cfDNA was feasible, but had limited sensitivity to detect all somatic mutations present in tissue. Digital PCR and mutant allele enrichment before NGS appeared to be more sensitive to detect somatic mutations.

Measuring intratumor heterogeneity by network entropy using RNA-seq data

Intratumor heterogeneity (ITH) is observed at different stages of tumor progression, metastasis and reouccurence, which can be important for clinical applications. We used RNA-sequencing data from tumor samples, and measured the level of ITH in terms of biological network states. To model complex relationships among genes, we used a protein interaction network to consider gene-gene dependency. ITH was measured by using an entropy-based distance metric between two networks, nJSD, with Jensen-Shannon Divergence (JSD). With nJSD, we defined transcriptome-based ITH (tITH). The effectiveness of tITH was extensively tested for the issues related with ITH using real biological data sets. Human cancer cell line data and single-cell sequencing data were investigated to verify our approach. Then, we analyzed TCGA pan-cancer 6,320 patients. Our result was in agreement with widely used genome-based ITH inference methods, while showed better performance at survival analysis. Analysis of mouse clonal evolution data further confirmed that our transcriptome-based ITH was consistent with genetic heterogeneity at different clonal evolution stages. Additionally, we found that cell cycle related pathways have significant contribution to increasing heterogeneity on the network during clonal evolution. We believe that the proposed transcriptome-based ITH is useful to characterize heterogeneity of a tumor sample at RNA level.

Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics

Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine.

The rise of genomic profiling in ovarian cancer

INTRODUCTION

Next-generation sequencing and advances in 'omics technology have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers. Areas covered: Once characterized only by histologic appearance and clinical behavior, we now understand many of the molecular phenotypes that underlie the different ovarian cancer subtypes. While the current approach to treatment involves standard cytotoxic therapies after cytoreductive surgery for all ovarian cancers regardless of histologic or molecular characteristics, focus has shifted beyond a 'one size fits all' approach to ovarian cancer. Expert commentary: Genomic profiling offers potentially 'actionable' opportunities for development of targeted therapies and a more individualized approach to treatment with concomitant improved outcomes and decreased toxicity.

The rise of genomic profiling in ovarian cancer

INTRODUCTION

Next-generation sequencing and advances in 'omics technology have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers. Areas covered: Once characterized only by histologic appearance and clinical behavior, we now understand many of the molecular phenotypes that underlie the different ovarian cancer subtypes. While the current approach to treatment involves standard cytotoxic therapies after cytoreductive surgery for all ovarian cancers regardless of histologic or molecular characteristics, focus has shifted beyond a 'one size fits all' approach to ovarian cancer. Expert commentary: Genomic profiling offers potentially 'actionable' opportunities for development of targeted therapies and a more individualized approach to treatment with concomitant improved outcomes and decreased toxicity.

Role of Local Ablative Therapy in Patients with Oligometastatic and Oligoprogressive Non-Small Cell Lung Cancer

Because of an improved understanding of lung cancer biology and improvement in systemic treatment, an oligometastatic state in which metastatic disease is present at a limited number of anatomic sites is being increasingly recognized. An oligoprogressive state, which is a similar but distinct entity, refers to disease progression at a limited number of anatomic sites, with continued response or stable disease at other sites of disease. Such an oligoprogressive state is best described in patients with NSCLC treated with molecular targeted therapy. Possible explanations for development of the oligoprogressive state include the presence of underlying clonal heterogeneity and extrinsic selection pressure due to the use of targeted therapy. Traditionally, local ablative therapy (LAT) has been limited to symptom palliation in patients with advanced NSCLC, but the presence of oligometastatic or oligoprogressive disease provides a unique opportunity to evaluate the role of LAT such as surgery, radiation therapy, radiofrequency ablation, or cryoablation. There is increasing evidence to support the clinical benefit of LAT in patients with NSCLC with limited metastatic disease and in selected individuals in whom resistance to targeted therapies develops. In the latter instance, adequate treatment of drug-resistant clones by LAT could potentially help in avoiding switching systemic therapy prematurely. This review focuses on the biology of oligometastatic and oligoprogressive NSCLC and describes the role of LAT in the treatment of these conditions.

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG_5-FU/L-OHP). Taking CRG_5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG_5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

Primary breast cancer cell culture yields intra-tumor heterogeneous subpopulations expressing exclusive patterns of receptor tyrosine kinases

Background

It has become evident that intra-tumor heterogeneity of breast cancer impact on several biological processes such as proliferation, migration, cell death and also might contribute to chemotherapy resistance. The expression of Receptor Tyrosine Kinases (RTKs) has not been analyzed in the context of intra-tumor heterogeneity in a primary breast cancer cell culture. Several subpopulations were isolated from the MBCDF (M serial-breast cancer ductal F line) primary breast cancer cells and were successfully maintained in culture and divided in two groups according to their morphology and RTKs expression pattern, and correlated with biological processes like proliferation, migration, anchorage-independent cell growth, and resistance to cytotoxic chemotherapy drugs and tyrosine kinase inhibitors (TKIs).

Methods

Subpopulations were isolated from MBCDF primary breast cancer cell culture by limiting dilution. RTKs and hormone receptors were examined by Western blot. Proliferation was measure by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide (MTT assay). Cell viability was evaluated by Crystal Violet. Migration was assessed using Boyden chambers. Anchorage-independent cell growth was evaluated by colony formation in soft agar.

Results

Several subpopulations were isolated from the MBCDF breast cancer cells that were divided into two groups according to their morphology. Analysis of RTKs expression pattern showed that HER1, HER3, c-Met and VEGFR2 were expressed exclusively in cells from group 1, but not in cells from group 2. PDGFR was expressed only in cells from group 2, but not in cells from group 1. HER2, HER4, c-Kit, IGF1-R were expressed in all subpopulations. Biological processes correlated with the RTKs expression pattern. Group 2 subpopulations present the highest rate of cell proliferation, migration and anchorage-independent cell growth. Analysis of susceptibility to chemotherapy drugs and TKIs showed that only Paclitaxel and Imatinib behaved differently between groups. Group 1-cells were resistant to both Paclitaxel and Imatinib.

Conclusions

We demonstrated that subpopulations from MBCDF primary cell culture could be divided into two groups according to their morphology and a RTKs excluding-expression pattern. The differences observed in RTKs expression correlate with the biological characteristics and chemoresistance of each group. These results suggest that intra-tumor heterogeneity contributes to generate groups of subpopulations with a more aggressive phenotype within the tumor.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2769-0) contains supplementary material, which is available to authorized users.

Detection of single cell heterogeneity in cancer

Single cell heterogeneity has already been highlighted in cancer classification, diagnosis, and treatment. Recent advanced technologies have gained more ability to reveal the heterogeneity on single cell level. In this review, we listed various detection targets applied in single cell study, including tumor tissue cells, circulating tumor cells (CTCs), disseminated tumor cells (DTCs), circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), and cancer stem cells (CSCs). We further discussed and compared detection methods using these detection targets in different fields to reveal single cell heterogeneity in cancer. We focused not only on the methods that have already been established and validated, but also on newly developed methods. In morphology and phenotype, the methods mainly included cell imaging and immune-staining. In genomics and proteomics, the main methods were single cell sequencing and single cell western blotting. Collectively, from using these methods, we can have a better understanding of the single cell variation, as well as what kind of variation it is and how the variation works. Our observations imply that study on single cell heterogeneity in cancer is an important step to precision medicine. The development of technologies in detection of single cell heterogeneity will be sure to improve the diagnosis and treatment in cancer.

Emerging power of proteomics for delineation of intrinsic tumor subtypes and resistance mechanisms to anti-cancer therapies

INTRODUCTION

Despite extreme genetic heterogeneity, tumors often show similar alterations in the expression, stability, and activation of proteins important in oncogenic signaling pathways. Thus, classifying tumor samples according to shared proteomic features may help facilitate the identification of cancer subtypes predictive of therapeutic responses and prognostic for patient outcomes. Meanwhile, understanding mechanisms of intrinsic and acquired resistance to anti-cancer therapies at the protein level may prove crucial to devising reversal strategies. Areas covered: Herein, we review recent advances in quantitative proteomic technology and their applications in studies to identify intrinsic tumor subtypes of various tumors, to illuminate mechanistic aspects of pharmacological and oncogenic adaptations, and to highlight interaction targets for anti-cancer compounds and cancer-addicted proteins. Expert commentary: Quantitative proteomic technologies are being successfully employed to classify tumor samples into distinct intrinsic subtypes, to improve existing DNA/RNA based classification methods, and to evaluate the activation status of key signaling pathways.

Deciphering and Targeting Oncogenic Mutations and Pathways in Breast Cancer

: Advances in DNA and RNA sequencing revealed substantially greater genomic complexity in breast cancer than simple models of a few driver mutations would suggest. Only very few, recurrent mutations or copy-number variations in cancer-causing genes have been identified. The two most common alterations in breast cancer are TP53 (affecting the majority of triple-negative breast cancers) and PIK3CA (affecting almost half of estrogen receptor-positive cancers) mutations, followed by a long tail of individually rare mutations affecting <1%-20% of cases. Each cancer harbors from a few dozen to a few hundred potentially high-functional impact somatic variants, along with a much larger number of potentially high-functional impact germline variants. It is likely that it is the combined effect of all genomic variations that drives the clinical behavior of a given cancer. Furthermore, entirely new classes of oncogenic events are being discovered in the noncoding areas of the genome and in noncoding RNA species driven by errors in RNA editing. In light of this complexity, it is not unexpected that, with the exception of HER2 amplification, no robust molecular predictors of benefit from targeted therapies have been identified. In this review, we summarize the current genomic portrait of breast cancer, focusing on genetic aberrations that are actively being targeted with investigational drugs.

IMPLICATIONS FOR PRACTICE

Next-generation sequencing is now widely available in the clinic, but interpretation of the results is challenging, and its impact on treatment selection is often limited. This work provides an overview of frequently encountered molecular abnormalities in breast cancer and discusses their potential therapeutic implications. This review emphasizes the importance of administering investigational targeted therapies, or off-label use of approved targeted drugs, in the context of a formal clinical trial or registry programs to facilitate learning about the clinical utility of tumor target profiling.

The content of mutant EGFR DNA correlates with response to EGFR-TKIs in lung adenocarcinoma patients with common EGFR mutations

This study aimed to elucidate the association of the content of mutant epidermal growth factor receptor (EGFR) deoxyribonucleic acid (DNA) with the treatment response to EGFR-tyrosine kinase inhibitor (TKI) and survival in patients with lung cancer.This retrospective cohort study included 77 lung adenocarcinoma patients with common EGFR mutations from December 2012 to February 2015. The content of mutant EGFR DNA in lung cancer tissues was determined using an Amplification Refractory Mutation System. The association of the amount of mutant EGFR DNA with treatment response, the clinical variables, and the progression-free survival (PFS) after EGFR-TKI therapy were evaluated.Using the amount of mutant EGR DNA above 4.77% as the cut-off value, the sensitivity to predict EGFR-TKI responder is 82.0% and the specificity is 75.0% (area under the curve [AUC]: 0.734, P = 0.003). The high content of mutant EGFR DNA is an independent factor associated with the response to EGFR-TKIs (odds ratio: 13.07, 95% confidence interval [CI]: 3.23-52.11, P = 0.0003). A significantly longer PFS was observed in the group with the high content of mutant EGFR DNA (26.3 months, 95% CI: 12.2-26.3) compared with the low content of mutant EGFR DNA groups (12.3 months, 95% CI: 5.7-14.8, P = 0.0155). A better predictive value of the content of mutant EGFR DNA was noted in patients with exon 19 deletions (AUC: 0.892, P < 0.0001) than exon 21 L858R mutations (AUC: 0.675, P = 0.0856).Our results show that the content of mutant EGFR DNA is associated with the clinical response to EGFR-TKIs, especially in patients with exon 19 deletions mutation.

Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity.

Targeting the Heterogeneity of Cancer with Individualized Neoepitope Vaccines

Somatic mutations binding to the patient's MHC and recognized by autologous T cells (neoepitopes) are ideal cancer vaccine targets. They combine a favorable safety profile due to a lack of expression in healthy tissues with a high likelihood of immunogenicity, as T cells recognizing neoepitopes are not shaped by central immune tolerance. Proteins mutated in cancer (neoantigens) shared by patients have been explored as vaccine targets for many years. Shared ("public") mutations, however, are rare, as the vast majority of cancer mutations in a given tumor are unique for the individual patient. Recently, the novel concept of truly individualized cancer vaccination emerged, which exploits the vast source of patient-specific "private" mutations. Concurrence of scientific advances and technological breakthroughs enables the rapid, cost-efficient, and comprehensive mapping of the "mutanome," which is the entirety of somatic mutations in an individual tumor, and the rational selection of neoepitopes. How to transform tumor mutanome data to actionable knowledge for tailoring individualized vaccines "on demand" has become a novel research field with paradigm-shifting potential. This review gives an overview with particular focus on the clinical development of such vaccines.

Micropapillary: A component more likely to harbour heterogeneous EGFR mutations in lung adenocarcinomas

The micropapillary (MP) subtype has recently been established to be a distinct marker of poor prognosis in lung adenocarcinomas (LACs). According to the 2015 WHO classification system, LAC constituents are required to be precisely reported. T790M mutation and an insertion in exon 20 (E20ins) are associated with EGFR-TKI resistance. A total of 211 LAC patients were involved in this study, and EGFR mutations were determined using an amplification refractory mutation system (ARMS). Sex, smoking history, lymph node status, and clinical stage differed significantly between the EGFR wild type and mutant groups (p < 0.05). The EGFR mutation occurred more frequently in female, non-smokers, ACs with papillary (85.7%) or MP components (91.4%) (p < 0.001). Twenty ACs with naïve T790M or E20ins were microdissected. The AC constituents metastasizing to lymph nodes exhibited a phenotype and EGFR status that was consistent with the primary loci constituents. Glomerulus-like solid components exhibited the same EGFR status as the surrounding T790M-mutated MP components. The MP and glomerulus-like portions in AC tumours exhibited a congenial EGFR status, but the acinar cells with papillary cells were heterogeneous. The naïve T790M mutants, although minor in the MP component, dramatically increased after EGFR-TKI therapy and indicate that the MP components feature intrinsic heterogeneity.

Primary Systemic Treatment in the Management of Operable Breast Cancer: Best Surgical Approach for Diagnosis, Biological Evaluation, and Research

Despite the ever-changing breast surgeon's technical role, the surgeon forms an indispensible link between imaging, diagnostics, pathology, and the medical oncologist. Biomarkers of prognosis, prediction of response, and resistance to treatments, including imaging, tissue and circulating markers apply to the primary diagnostic and treatment settings as well as scenarios which include disease recurrence, both in the early and advanced settings. Whether it is via the diagnostic clinic referred by the primary care physician or via a breast screening service, primary early breast cancer is referred for initial treatment and/or diagnosis and currently remains the domain of the surgical oncologist. The surgeon is privileged by this unique "window of opportunity" to consider the biological aspects of the diagnosis and guide the patient appropriately toward initial therapy, only one of which is primary surgery. Options of neoadjuvant endocrine, cytotoxic, or targeted therapy as either standard of care or else in the clinical trial context should be considered to optimize treatment in all patients.

Actionable mutations in plasma cell-free DNA in patients with advanced cancers referred for experimental targeted therapies

Cell-free (cf) DNA in the plasma of cancer patients offers an easily obtainable source of biologic material for mutation analysis. Plasma samples from 157 patients with advanced cancers who progressed on systemic therapy were tested for 21 mutations in BRAF, EGFR, KRAS, and PIK3CA using the BEAMing method and results were compared to mutation analysis of archival tumor tissue from a CLIA-certified laboratory obtained as standard of care from diagnostic or therapeutic procedures. Results were concordant for archival tissue and plasma cfDNA in 91% cases for BRAF mutations (kappa = 0.75, 95% confidence interval [CI] 0.63 – 0.88), in 99% cases for EGFR mutations (kappa = 0.90, 95% CI 0.71– 1.00), in 83% cases for KRAS mutations (kappa = 0.67, 95% CI 0.54 – 0.80) and in 91% cases for PIK3CA mutations (kappa = 0.65, 95% CI 0.46 – 0.85). Patients (n = 41) with > 1% of KRAS mutant cfDNA had a shorter median survival compared to 20 patients with </= 1% of KRAS mutant DNA (4.8 vs. 7.3 months, p = 0.008). Similarly, 67 patients with > 1% of mutant cfDNA (BRAF, EGFR, KRAS, or PIK3CA) had a shorter median survival compared to 33 patients with </= 1% of mutant cfDNA (5.5 vs. 9.8 months, p = 0.001), which was confirmed in multivariable analysis.

Multiple cellular origins and molecular evolution of intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy associated with unfavorable prognosis and for which no effective treatments are available. Its molecular pathogenesis is poorly understood. Genome-wide sequencing and high-throughput technologies have provided critical insights into the molecular basis of ICC while sparking a heated debate on the cellular origin. Cancer exhibits variabilities in origin, progression and cell biology. Recent evidence suggests that ICC has multiple cellular origins, including differentiated hepatocytes; intrahepatic biliary epithelial cells (IBECs)/cholangiocytes; pluripotent stem cells, such as hepatic stem/progenitor cells (HPCs) and biliary tree stem/progenitor cells (BTSCs); and peribiliary gland (PBG). However, both somatic mutagenesis and epigenomic features are highly cell type-specific. Multiple cellular origins may have profoundly different genomic landscapes and key signaling pathways, driving phenotypic variation and thereby posing significant challenges to personalized medicine in terms of achieving the optimal drug response and patient outcome. Considering this information, we have summarized the latest experimental evidence and relevant literature to provide an up-to-date view of the cellular origin of ICC, which will contribute to establishment of a hierarchical model of carcinogenesis and allow for improvement of the anatomical-based classification of ICC. These new insights have important implications for both the diagnosis and treatment of ICC patients.

"Combo" nanomedicine: Co-delivery of multi-modal therapeutics for efficient, targeted, and safe cancer therapy

The dynamic and versatile nature of diseases such as cancer has been a pivotal challenge for developing efficient and safe therapies. Cancer treatments using a single therapeutic agent often result in limited clinical outcomes due to tumor heterogeneity and drug resistance. Combination therapies using multiple therapeutic modalities can synergistically elevate anti-cancer activity while lowering doses of each agent, hence, reducing side effects. Co-administration of multiple therapeutic agents requires a delivery platform that can normalize pharmacokinetics and pharmacodynamics of the agents, prolong circulation, selectively accumulate, specifically bind to the target, and enable controlled release in target site. Nanomaterials, such as polymeric nanoparticles, gold nanoparticles/cages/shells, and carbon nanomaterials, have the desired properties, and they can mediate therapeutic effects different from those generated by small molecule drugs (e.g., gene therapy, photothermal therapy, photodynamic therapy, and radiotherapy). This review aims to provide an overview of developing multi-modal therapies using nanomaterials ("combo" nanomedicine) along with the rationale, up-to-date progress, further considerations, and the crucial roles of interdisciplinary approaches.

Mathematical Modeling of Therapy-induced Cancer Drug Resistance: Connecting Cancer Mechanisms to Population Survival Rates

Drug resistance significantly limits the long-term effectiveness of targeted therapeutics for cancer patients. Recent experimental studies have demonstrated that cancer cell heterogeneity and microenvironment adaptations to targeted therapy play important roles in promoting the rapid acquisition of drug resistance and in increasing cancer metastasis. The systematic development of effective therapeutics to overcome drug resistance mechanisms poses a major challenge. In this study, we used a modeling approach to connect cellular mechanisms underlying cancer drug resistance to population-level patient survival. To predict progression-free survival in cancer patients with metastatic melanoma, we developed a set of stochastic differential equations to describe the dynamics of heterogeneous cell populations while taking into account micro-environment adaptations. Clinical data on survival and circulating tumor cell DNA (ctDNA) concentrations were used to confirm the effectiveness of our model. Moreover, our model predicted distinct patterns of dose-dependent synergy when evaluating a combination of BRAF and MEK inhibitors versus a combination of BRAF and PI3K inhibitors. These predictions were consistent with the findings in previously reported studies. The impact of the drug metabolism rate on patient survival was also discussed. The proposed model might facilitate the quantitative evaluation and optimization of combination therapeutics and cancer clinical trial design.

High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control. Here we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM revealed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo.

Cancer stem cells may contribute to the difficulty in treating cancer

Tumour heterogeneity is a phenomenon where each cell that makes up a tumour, contains mutations that differ from that of other cells in the tumour. The clonal evolution and cancer stem cell theories of cancer formation, have been used to explain tumour heterogeneity. The theories both point to the existence of cells within a tumour that are capable of initiating the tumour in a different location. While the clonal evolution theory argues that all cells within a tumour possess this ability, the cancer stem cell theory argues that only a few cells (cancer stem cells or CSCs) within the tumour possess this ability to seed the tumour in a different location. Data supporting the cancer stem cell theory is accumulating. Researchers have targeted these CSCs therapeutically, hypothesizing that since these CSCs are the ‘drivers’ of tumour progression, their death may inhibit tumour progression. This was foiled by tumour cell plasticity, a phenomenon whereby a non-CSC spontaneously de-differentiates into a CSC. Researchers are now working on combinations that kill both CSCs and non-CSCs as well as drugs that prevent non-CSC-to-CSC transition. This review concisely describes CSCs and how they contribute to the difficulty in treating cancer.

Cisplatin in the modern era: The backbone of first-line chemotherapy for non-small cell lung cancer

The treatment of advanced non-small cell lung cancer (NSCLC) may be changing, but the cisplatin-based doublet remains the foundation of treatment for the majority of patients with advanced NSCLC. In this respect, changes in practice to various aspects of cisplatin use, such as administration schedules and the choice of methods and frequency of monitoring for toxicities, have contributed to an incremental improvement in patient management and experience. Chemoresistance, however, limits the clinical utility of this drug in patients with advanced NSCLC. Better understanding of the molecular mechanisms of cisplatin resistance, identification of predictive markers and the development of newer, more effective and less toxic platinum agents is required. In addition to maximising potential benefits from advances in molecular biology and associated therapeutics, modification of existing cisplatin-based treatments can still lead to improvements in patient outcomes and experiences.

Pluripotency markers are differentially induced by MEK inhibition in thyroid and melanoma BRAFV600E cell lines

Oncogenic mutations in BRAF are common in melanoma and thyroid carcinoma and drive constitutive activation of the MAPK pathway. Molecularly targeted therapies of this pathway improves survival compared to chemotherapy; however, responses tend to be short-lived as resistance invariably occursCell line models of melanoma and thyroid carcinoma, +/− BRAF^V600E activating mutation, were treated with the MEK inhibitor PD0325901. Treated and naive samples were assayed for expression of key members of the MAPK pathway. Global microRNA expression profiling of naive and resistant cells was performed via next generation sequencingand indicated pluripotency pathways in resistance. Parental cell lines were progressed to holoclones to confirm the miRNA stemness profileMembers of the MIR302/373/374/520 family of embryonic stem cell specific cell cycle regulating (ESCC) microRNAs were identified as differentially expressed between resistant BRAF^V600E melanoma and thyroid cell lines. Upregulated expression of gene and protein stemness markers, upregulated expression of MAPK pathway genes and downregulation of the ESCC MIR302 cluster in BRAF^V600E melanoma indicated an increased stem-like phenotype in resistant BRAF^V600E melanoma. Conversely, downregulated expression of gene and protein stemness markers, downregulated expression of MAPK pathway genes, upregulation of the ESCC MIR520 cluster, reeexpression of cell surface receptors, and induced differentiation-associated morphology in resistant BRAF^V600E indicate a differentiated phenotype associated with MEK inhibitor resistance in BRAF^V600E thyroid cellsThe differential patterns of resistance observed between BRAF^V600E melanoma and thyroid cell lines may reflect tissue type or de novo differentiation, but could have significant impact on the response of primary and metastatic cells to MEK inhibitor treatment. This study provides a basis for the investigation of the cellular differentiation/self-renewal access and its role in resistance to MEK inhibition.

The Upregulation of PI3K/Akt and MAP Kinase Pathways is Associated with Resistance of Microtubule-Targeting Drugs in Prostate Cancer

Resistance is a significant limitation to the effectiveness of cancer therapies. The PI3K/Akt and MAP kinase pathways play important roles in a variety of normal cellular processes and tumorigenesis. This study is designed to explore the relationship of these signaling pathways with multidrug resistance in prostate cancer (PCa). The PI3K/Akt and MAP kinase pathways were investigated utilizing paclitaxel resistant DU145-TxR PCa cells and their parental non-resistant DU145 cells to determine their relationship with resistance to paclitaxel and other anticancer drugs. Our results demonstrate that the PI3K/Akt and MAP kinase pathways are upregulated in DU145-TxR cells compared to the DU145 cells. Inactivating these pathways using the PI3K/Akt pathway inhibitor LY294002 or the MAP kinase pathway inhibitor PD98059 renders the DU145-TxR cells more sensitive to paclitaxel. We investigated the effects of these inhibitors on other anticancer drugs including docetaxel, vinblastine, doxorubicin, 10-Hydroxycamptothecin (10-HCPT) and cisplatin and find that both inhibitors induces DU145-TxR cells to be more sensitive only to the microtubule-targeting drugs (paclitaxel, docetaxel and vinblastine). Furthermore, the treatment with these inhibitors induces cleaved-PARP production in DU145-TxR cells, suggesting that apoptosis induction might be one of the mechanisms for the reversal of drug resistance. In conclusion, the PI3K/Akt and MAP kinase pathways are associated with resistance to multiple chemotherapeutic drugs. Inactivating these pathways renders these PCa cells more sensitive to microtubule-targeting drugs such as paclitaxel, docetaxel and vinblastine. Combination therapies with novel inhibitors of these two signaling pathways potentially represents a more effective treatment for drug resistant PCa.

Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia

Clonal evolution in cancer-the selection for and emergence of increasingly malignant clones during progression and therapy, resulting in cancer metastasis and relapse-has been highlighted as an important phenomenon in the biology of leukemia and other cancers. Tracking mutant alleles to determine clonality from diagnosis to relapse or from primary site to metastases in a sensitive and quantitative manner is most often performed using next-generation sequencing. Such methods determine clonal frequencies by extrapolation of allele frequencies in sequencing data of DNA from the metagenome of bulk tumor samples using a set of assumptions. The computational framework that is usually used assumes specific patterns in the order of acquisition of unique mutational events and heterozygosity of mutations in single cells. However, these assumptions are not accurate for all mutant loci in acute myeloid leukemia (AML) samples. To assess whether current models of clonal diversity within individual AML samples are appropriate for common mutations, we developed protocols to directly genotype AML single cells. Single-cell analysis demonstrates that mutations of FLT3 and NPM1 occur in both homozygous and heterozygous states, distributed among at least nine distinct clonal populations in all samples analyzed. There appears to be convergent evolution and differential evolutionary trajectories for cells containing mutations at different loci. This work suggests an underlying tumor heterogeneity beyond what is currently understood in AML, which may be important in the development of therapeutic approaches to eliminate leukemic cell burden and control clonal evolution-induced relapse.

Targeting tumor microenvironment with PEG-based amphiphilic nanoparticles to overcome chemoresistance

Multidrug resistance is one of the biggest obstacles in the treatment of cancer. Recent research studies highlight that tumor microenvironment plays a predominant role in tumor cell proliferation, metastasis, and drug resistance. Hence, targeting the tumor microenvironment provides a novel strategy for the evolution of cancer nanomedicine. The blooming knowledge about the tumor microenvironment merging with the design of PEG-based amphiphilic nanoparticles can provide an effective and promising platform to address the multidrug resistant tumor cells. This review describes the characteristic features of tumor microenvironment and their targeting mechanisms with the aid of PEG-based amphiphilic nanoparticles for the development of newer drug delivery systems to overcome multidrug resistance in cancer cells.

FROM THE CLINICAL EDITOR

Cancer is a leading cause of death worldwide. Many cancers develop multidrug resistance towards chemotherapeutic agents with time and strategies are urgently needed to combat against this. In this review article, the authors discuss the current capabilities of using nanomedicine to target the tumor microenvironments, which would provide new insight to the development of novel delivery systems for the future.

Treatment Algorithms Based on Tumor Molecular Profiling: The Essence of Precision Medicine Trials

With the advent of high-throughput molecular technologies, several precision medicine (PM) studies are currently ongoing that include molecular screening programs and PM clinical trials. Molecular profiling programs establish the molecular profile of patients' tumors with the aim to guide therapy based on identified molecular alterations. The aim of prospective PM clinical trials is to assess the clinical utility of tumor molecular profiling and to determine whether treatment selection based on molecular alterations produces superior outcomes compared with unselected treatment. These trials use treatment algorithms to assign patients to specific targeted therapies based on tumor molecular alterations. These algorithms should be governed by fixed rules to ensure standardization and reproducibility. Here, we summarize key molecular, biological, and technical criteria that, in our view, should be addressed when establishing treatment algorithms based on tumor molecular profiling for PM trials.

Analysis of ESR1 mutation in circulating tumor DNA demonstrates evolution during therapy for metastatic breast cancer

Acquired ESR1 mutations are a major mechanism of resistance to aromatase inhibitors (AIs). We developed ultra high-sensitivity multiplex digital polymerase chain reaction assays for ESR1 mutations in circulating tumor DNA (ctDNA) and investigated the clinical relevance and origin of ESR1 mutations in 171 women with advanced breast cancer. ESR1 mutation status in ctDNA showed high concordance with contemporaneous tumor biopsies and was accurately assessed in samples shipped at room temperature in preservative tubes. ESR1 mutations were found exclusively in estrogen receptor-positive breast cancer patients previously exposed to AI. Patients with ESR1 mutations had a substantially shorter progression-free survival on subsequent AI-based therapy [hazard ratio, 3.1; 95% confidence interval (CI), 1.9 to 23.1; P = 0.0041]. ESR1 mutation prevalence differed markedly between patients who were first exposed to AI during the adjuvant and metastatic settings [5.8% (3 of 52) versus 36.4% (16 of 44), respectively; P = 0.0002]. In an independent cohort, ESR1 mutations were identified in 0% (0 of 32; 95% CI, 0 to 10.9) tumor biopsies taken after progression on adjuvant AI. In a patient with serial sampling, ESR1 mutation was selected during metastatic AI therapy to become the dominant clone in the cancer. ESR1 mutations can be robustly identified with ctDNA analysis and predict for resistance to subsequent AI therapy. ESR1 mutations are rarely acquired during adjuvant AI but are commonly selected by therapy for metastatic disease, providing evidence that mechanisms of resistance to targeted therapy may be substantially different between the treatment of micrometastatic and overt metastatic cancer.

Toward the Broad Adoption of 3D Tumor Models in the Cancer Drug Pipeline

Despite a cost of approximately $1 billion to develop a new cancer drug, about 90% of drugs that enter clinical trials fail. A tremendous opportunity exists to streamline the drug selection and testing process, and innovative approaches promise to reduce the burdensome cost of health care for those suffering from cancer. There is great potential for 3D models of human tumors to complement more traditional testing methods; however, the shift from 2D to 3D assays at early stages of the drug discovery and development process is far from widely accepted. 3D platforms range from simple tumor spheroids to more complex microfluidic hydrogels that better mimic the tumor microenvironment. While several companies have developed and patented advanced high-throughput 3D platforms for drug screening, their cost and complexity have limited their adoption as an industry standard. In this review, we will highlight the various tumor platforms that have been developed, emphasizing the approaches that have successfully led to commercial products. We will then consider potential directions toward more relevant tumor models, advantages of the adoption of such platforms within the drug development and screening process, and new opportunities in personalized medicine that such platforms will uniquely enable.

Rare discrepancies in a driver gene alteration within histologically heterogeneous primary lung cancers

OBJECTIVES

Most lung adenocarcinomas consist of mixtures of histological subtypes harboring different frequencies of driver gene mutations. However, little is known about intratumoral heterogeneity(ITH) within histologically heterogeneous primary lung cancers. Investigating key driver genes in respective morphological pattern is crucial to personalized treatment.

METHODS

Morphologically different areas within the same surgically resected adenocarcinomas were extracted from tissues to analyze gene status in each growth pattern. Driver genes, epidermal growth factor receptor (EGFR), KRAS and EML4-ALK, were assessed by assays with different sensitivities.

RESULTS

Seventy-nine consecutive eligible patients harboring a driver gene (EGFR=65; KRAS=10; EML4-ALK=4) were enrolled. For EGFR mutations, ITH occurred in 13.3% (8/60) by direct sequencing (DS) and 1.7% (1/60) by amplification refractory mutation system (ARMS) (P=0.016) among adenocarcinomas, but consistent within five adeno-squamous cell carcinomas by both methods. ITH among KRAS mutations were detected in 20% (2/10) by DS, whereas consistent (10/10) by high resolution melting. No discrepancies in EML4-ALK rearrangements existed according to fluorescence in situ hybridization.

CONCLUSION

Rare ITHs of EGFR/KRAS/EML4-ALK alterations within histologically heterogeneous primary lung adenocarcinomas existed by methods with higher sensitivity. Discrepancies might be due to abundance of mutant tumor cells and detection assays.

Characteristics of Tumor Infiltrating Lymphocyte and Circulating Lymphocyte Repertoires in Pancreatic Cancer by the Sequencing of T Cell Receptors

Pancreatic cancer has a poor prognosis and few effective treatments. The failure of treatment is partially due to the high heterogeneity of cancer cells within the tumor. T cells target and kill cancer cells by the specific recognition of cancer-associated antigens. In this study, T cells from primary tumor and blood of sixteen patients with pancreatic cancer were characterized by deep sequencing. T cells from blood of another eight healthy volunteers were also studied as controls. By analyzing the complementary determining region 3 (CDR3) gene sequence, we found no significant differences in the T cell receptor (TCR) repertoires between patients and healthy controls. Types and length of CDR3 were similar among groups. However, two clusters of patients were identified according to the degree of CDR3 overlap within tumor sample group. In addition, clonotypes with low frequencies were found in significantly higher numbers in primary pancreatic tumors compared to blood samples from patients and healthy controls. This study is the first to characterize the TCR repertoires of pancreatic cancers in both primary tumors and matched blood samples. The results imply that specific types of pancreatic cancer share potentially important immunological characteristics.