The EGFR family members sustain the neoplastic phenotype of ALK+ lung adenocarcinoma via EGR1

Oncogenic EML4-ALK assemblies suppress growth factor perception and modulate drug tolerance

Drug resistance remains a challenge for targeted therapy of cancers driven by EML4-ALK and related fusion oncogenes. EML4-ALK forms cytoplasmic protein condensates, which result from networks of interactions between oncogene and adapter protein multimers. While these assemblies are associated with oncogenic signaling, their role in drug response is unclear. Here, we use optogenetics and live-cell imaging to find that EML4-ALK assemblies suppress transmembrane receptor tyrosine kinase (RTK) signaling by sequestering RTK adapter proteins including GRB2 and SOS1. Furthermore, ALK inhibition, while suppressing oncogenic signaling, simultaneously releases the sequestered adapters and thereby resensitizes RTK signaling. Resensitized RTKs promote rapid and pulsatile ERK reactivation that originates from paracrine ligands shed by dying cells. Reactivated ERK signaling promotes cell survival, which can be counteracted by combination therapies that block paracrine signaling. Our results identify a regulatory role for RTK fusion assemblies and uncover a mechanism of tolerance to targeted therapies.

MATES: a deep learning-based model for locus-specific quantification of transposable elements in single cell

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either 'best-mapped' or 'random-mapped' locations and categorize them at the subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.

Sequencing of cutaneous squamous cell carcinoma primary tumors and patient-matched metastases reveals ALK as a potential driver in metastases and low mutational concordance in immunocompromised patients

Cutaneous squamous cell carcinoma is a common skin cancer that is responsible for 1,000,000 cases and up to 9,000 deaths annually in the United States. Metastases occur in 2–5% of patients and are responsible for significant morbidity and mortality. The objective of this study is to perform targeted next-generation sequencing on a cohort of squamous cell carcinoma primary tumors and patient-matched lymph node metastases. An oncology 76-gene panel was run from formalin-fixed paraffin-embedded samples of patient-matched primary squamous cell carcinomas (10) and resultant metastases (10). ALK was discovered to be a driver mutation in metastases using two different algorithms, oncoCLUSTand dNdScv. Mutational concordance between primary tumors and metastases was notably lower in immunosuppressed patients, especially among pathogenic mutations (41.7% vs. 83.3%, P = 0.01). Sequencing of matched squamous cell carcinoma primary tumors and lymph node metastases identified genes and pathways that may have clinical importance, most notably ALK as a potential driver mutation of metastasis. Sequencing of both primary tumors and metastases may improve the efficacy of targeted therapies.

Resistance to anaplastic lymphoma kinase inhibitors: knowing the enemy is half the battle won

Anaplastic lymphoma kinase (ALK) translocations are responsible of neoplastic transformation in a limited subset of non-small cell lung cancer (NSCLC) patients. In recent years outcomes of these patients improved due to the development and clinical availability of specific and extremely active targeted therapies [i.e., next-generation Tyrosine Kinase Inhibitors (TKI)]: ALK+ patients are now reaching impressive results when treated with more potent inhibitors upfront with an average median progression-free survival (mPFS) around 35 months. However, under drug pressure, cancer cells develop resistance and patients eventually progress. Multiple mechanisms of intrinsic or acquired resistance have been extensively characterized. Less potent ALK inhibitors (ALKi)—like crizotinib—usually tend to induce a large spectrum of secondary intra-kinase mutations; however, these alterations may be observed also after sequential administration of multiple ALKi. Noteworthy, neoplastic cells may evade ALK targeting through a myriad of different mechanisms involving cell-stroma interaction, activation of parallel signaling pathways, intracellular downstream adaptation and histological reshaping, as relevant molecular events. Often these phenomena are restricted to a limited number of cases or even can be patient-specific, thus hindering the development of therapeutic strategies largely applicable. Consequently, the recognition of specific resistance mechanisms seldom translates in clinical opportunities. Management of ALK+ patients is drastically changed and deciphering the molecular biology underlying this disease during treatment is of paramount relevance. The bedrock of resistance to TKI is that, after the diagnosis, we face with a different disease that needs to be re-characterized through tissue or/and liquid biopsies. Understanding molecular pathways driving the resistant phenotype will give us the chance to know what we are dealing with and, rather than choose an empirical approach, will help us to properly define the best targeted treatment for these patients.

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

Oct4 upregulates osteopontin via Egr1 and is associated with poor outcome in human lung cancer

Background

Roles of cancer stem cells and early growth response gene 1 (Egr1) in carcinogenesis have been extensively studied in lung cancer. However, the role of Egr1 in the metastasis of lung cancer remains undetermined, especially in regard to stem cell-related pathways.

Methods

Egr1, osteopontin (OPN) and Oct4 expression in human lung cancer was determined by performing immunohistochemistry. Immunoblotting, ELISA, luciferase reporter assay, chromatin immunoprecipitation assay and RT-PCR were performed to validate the regulation of Oct4-Egr1-OPN axis. Moreover, the effect of Oct4-Egr1-OPN axis on lung cancer progression was evaluated by cell migration assay and mice study.

Results

We detected Oct4, Egr1, and OPN expression in clinical specimens from 79 lung cancer patients, including 72 adenocarcinomas and 7 squamous cell carcinomas. High expression of Oct4, Egr1, and OPN accounted for 53, 51, and 57% of the patients, respectively. All of the three biomarkers were positively correlated in clinical human lung cancer. Patients with high expression of OPN were significantly associated with shorter disease-free survivals than those with low expression of OPN (p < 0.05). In lung cancer cells, Oct4 transactivated the Egr1 promoter and upregulated Egr1 expression. In a human lung cancer xenograft model, Oct4-overexpressing tumors expressed elevated levels of Egr1. Furthermore, overexpression of Oct4 in lung cancer cells increased the metastatic potential.

Conclusions

Egr1 exerts a promoting effect on cancer metastasis in Oct4-overexpressing lung cancer. Thus, therapeutic strategies targeting the Oct4/Egr1/OPN axis may be further explored for the treatment of lung cancer, especially when lung cancer is refractory to conventional treatment due to cancer stem cells.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-6014-5) contains supplementary material, which is available to authorized users.

Herbal formula Yangyinjiedu induces lung cancer cell apoptosis via activation of early growth response 1

Traditional Chinese Medicine (TCM) has been extensively used in clinical practices and proven to be effective against cancer. However, the underlying mechanisms remain to be investigated. In this study, we examined the anticancer activities of Chinese herbal formula Yangyinjiedu (YYJD) and found that YYJD exhibits cytotoxicity against lung cancer cells. Transcriptome analysis indicated that 2178 genes were differentially expressed (P < 0.05) upon YYJD treatment, with 1464 being (67.2%) up‐regulated. Among these, we found that the tumour suppressor early growth response 1 (EGR1) is the most activated. We demonstrated that EGR1 contributes to YYJD‐induced apoptosis in A549. Through dissecting EGR1‐associated transcriptional network, we identified 275 genes as EGR1 direct targets, some targets are involved in apoptosis. Lastly, we observed that YYJD enhances EGR1 expression and induces cell death in tumour xenografts. Collectively, these findings suggest that YYJD exerts its anticancer activities through EGR1 activation, thus providing the evidence for its potential clinical application for lung cancer patients.

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases

Identifying hyperactive kinases in cancer is crucial for individualized treatment with specific inhibitors. Kinase activity can be discerned from global protein phosphorylation profiles obtained with mass spectrometry-based phosphoproteomics. A major challenge is to relate such profiles to specific hyperactive kinases fueling growth/progression of individual tumors. Hitherto, the focus has been on phosphorylation of either kinases or their substrates. Here, we combined label-free kinase-centric and substrate-centric information in an Integrative Inferred Kinase Activity (INKA) analysis. This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase-substrate networks in a single biological sample. To demonstrate utility, we analyzed (i) cancer cell lines with known oncogenes, (ii) cell lines in a differential setting (wild-type versus mutant, +/- drug), (iii) pre- and on-treatment tumor needle biopsies, (iv) cancer cell panel with available drug sensitivity data, and (v) patient-derived tumor xenografts with INKA-guided drug selection and testing. These analyses show superior performance of INKA over its components and substrate-based single-sample tool KARP, and underscore target potential of high-ranking kinases, encouraging further exploration of INKA's functional and clinical value.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

Oncogenic kinase fusions: an evolving arena with innovative clinical opportunities

Cancer biology relies on intrinsic and extrinsic deregulated pathways, involving a plethora of intra-cellular and extra-cellular components. Tyrosine kinases are frequently deregulated genes, whose aberrant expression is often caused by major cytogenetic events (e.g. chromosomal translocations). The resulting tyrosine kinase fusions (TKFs) prompt the activation of oncogenic pathways, determining the biological and clinical features of the associated tumors. First reported half a century ago, oncogenic TKFs are now found in a large series of hematologic and solid tumors. The molecular basis of TKFs has been thoroughly investigated and tailored therapies against recurrent TKFs have recently been developed. This review illustrates the biology of oncogenic TKFs and their role in solid as well as hematological malignancies. We also address the therapeutic implications of TKFs and the many open issues concerning their clinical impact.

Oncogenic ALK regulates EMT in non-small cell lung carcinoma through repression of the epithelial splicing regulatory protein 1

A subset of Non-Small Cell Lung Carcinoma (NSCLC) carries chromosomal rearrangements involving the Anaplastic Lymphoma Kinase (ALK) gene. ALK-rearranged NSCLC are typically adenocarcinoma characterized by a solid signet-ring cell pattern that is frequently associated with a metastatic phenotype. Recent reports linked the presence of ALK rearrangement to an epithelial-mesenchymal transition (EMT) phenotype in NSCLC, but the extent and the mechanisms of an ALK-mediated EMT in ALK-rearranged NSCLC are largely unknown. We found that the ALK-rearranged H2228 and DFCI032, but not the H3122, cell lines displayed a mesenchymal phenotype. In these cell lines, oncogenic ALK activity dictated an EMT phenotype by directly suppressing E-cadherin and up-regulating vimentin expression, as well as expression of other genes involved in EMT. We found that the epithelial splicing regulatory protein 1 (ESRP1), a key regulator of the splicing switch during EMT, was repressed by EML4-ALK activity. The treatment of NSCLC cells with ALK tyrosine kinase inhibitors (TKIs) led to up-regulation of ESRP1 and E-cadherin, thus reverting the phenotype from mesenchymal to epithelial (MET). Consistently, ESRP1 knock-down impaired E-cadherin up-regulation upon ALK inhibition, whereas enforced expression of ESRP1 was sufficient to increase E-cadherin expression. These findings demonstrate an ALK oncogenic activity in the regulation of an EMT phenotype in a subset of NSCLC with potential implications for the biology of ALK-rearranged NSCLC in terms of metastatic propensity and resistance to therapy.

Epitope mapping of spontaneous autoantibodies to anaplastic lymphoma kinase (ALK) in non-small cell lung cancer

The anaplastic lymphoma kinase (ALK) is recognized by the immune system as a tumor antigen, and preclinical evidence suggests that ALK-rearranged NSCLCs can also be successfully targeted immunologically using vaccine-based approaches. In contrast to ALK-rearranged lymphomas, the frequency and clinical significance of spontaneous ALK immune responses in patients with ALK-rearranged NSCLCs are largely unknown. We developed an enzyme-linked immunosorbent assay (ELISA) to measure anti-ALK antibody levels and mapped specific peptide epitope sequences within the ALK cytoplasmic domain in patients with non-small cell lung cancer. The ELISA method showed good correlation with ALK antibody titers measured with a standard immunocytochemical approach. Strong anti-ALK antibody responses were detected in 9 of 53 (17.0%) ALK-positive NSCLC patients and in 0 of 38 (0%) ALK-negative NSCLC patients (P<0.01), and the mean antibody levels were significantly higher in ALK-positive than in ALK-negative NSCLC patients (P=0.02). Across individual patients, autoantibodies recognized different epitopes in the ALK cytoplasmic domain, most of which clustered outside the tyrosine kinase domain. Whether the presence of high ALK autoantibody levels confers a more favorable prognosis in this patient population warrants further investigation.

Identification of microRNAs involved in gefitinib resistance of non-small-cell lung cancer through the insulin-like growth factor receptor 1 signaling pathway

Multiple clinical and experimental studies have suggested that epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) may be effective at treating advanced non-small cell lung cancer (NSCLC), however, the molecular basis of primary resistance to EGFR-TKIs in NSCLC remains unclear. In the current study, the insulin-like growth factor 1 receptor (IGF-1R) gene in the gefitinib-resistant human lung adenocarcinoma epithelial cell line A549 (A549/GR) was silenced using small interfering RNA (siRNA) in order to determine the role of microRNA (miRNA) in the development of resistance against epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in lung adenocarcinoma. The relative gefitinib-resistant capacity in A549 and A549/GR cells was determined using a cell counting kit 8. A549/GR cells were transfected with chemically synthesized siRNA to silence the IGF-1R gene. A total of 48 h after siRNA transfection, IGF-1R expression in A549/GR cells was evaluated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. miRNA expression in A549/GR cells and A549/GR cells with silenced IGF-1R was analyzed using a miRNA microarray. The microarray results of 10 miRNAs were then compared with the results of RT-qPCR. The results demonstrated that the gefitinib-resistance capacity of A549/GR cells was six times higher than that of A549 cells. Additionally, RT-qPCR and western blotting demonstrated that the IGF-1R gene in A549/GR cells was successfully silenced by siRNA. The highest silencing rate (72%) of the IGF-1R gene was obtained using siRNA-2. The microarray identified 72 miRNAs with significantly different expression in A549/GR cells with silenced IGF-1R compared with A549/GR cells. Of the 72 differentially expressed miRNAs, 13 miRNAs (including miR-497-3p and miR-1273c) were up-regulated and 59 miRNAs (including miR-361-3p and miR-345-3p) were down-regulated in A549/GR cells with silenced IGF-1R compared with A549/GR cells. The changes in the expression of 10 different miRNAs were confirmed by RT-qPCR. Thus, the present study successfully established an A549/GR cell line with silenced IGF-1R. The results suggest that a number of miRNAs associated with the IGF-1R signaling pathway, including miR-497-3p and miR-144-5p, were involved in the development of resistance against EGFR-TKIs in A549 cells. These miRNAs may provide novel targets to treat lung adenocarcinoma exhibiting resistance against EGFR-TKIs.

EGFR Mediates Responses to Small-Molecule Drugs Targeting Oncogenic Fusion Kinases

Oncogenic kinase fusions of ALK, ROS1, RET, and NTRK1 act as drivers in human lung and other cancers. Residual tumor burden following treatment of ALK or ROS1⁺ lung cancer patients with oncogene-targeted therapy ultimately enables the emergence of drug-resistant clones, limiting the long-term effectiveness of these therapies. To determine the signaling mechanisms underlying incomplete tumor cell killing in oncogene-addicted cancer cells, we investigated the role of EGFR signaling in drug-naïve cancer cells harboring these oncogene fusions. We defined three distinct roles for EGFR in the response to oncogene-specific therapies. First, EGF-mediated activation of EGFR blunted fusion kinase inhibitor binding and restored fusion kinase signaling complexes. Second, fusion kinase inhibition shifted adaptor protein binding from the fusion oncoprotein to EGFR. Third, EGFR enabled bypass signaling to critical downstream pathways such as MAPK. While evidence of EGFR-mediated bypass signaling has been reported after ALK and ROS1 blockade, our results extended this effect to RET and NTRK1 blockade and uncovered the other additional mechanisms in gene fusion-positive lung cancer cells, mouse models, and human clinical specimens before the onset of acquired drug resistance. Collectively, our findings show how EGFR signaling can provide a critical adaptive survival mechanism that allows cancer cells to evade oncogene-specific inhibitors, providing a rationale to cotarget EGFR to reduce the risks of developing drug resistance. Cancer Res; 77(13); 3551-63. ©2017 AACR.

The Host Cell Transcription Factor EGR1 Is Induced by Bacteria through the EGFR-ERK1/2 Pathway

The essential first step in bacterial colonization is adhesion to the host epithelial cells. The early host-responses post-bacterial adhesions are still poorly understood. Early growth response 1 (EGR1) is an early response transcriptional regulator that can be rapidly induced by various environmental stimuli. Several bacteria can induce EGR1 expression in host cells, but the involved bacterial characteristics and the underlying molecular mechanisms of this response are largely unknown. Here, we show that EGR1 can be induced in host epithelial cells by different species of bacteria independent of the adherence level, Gram-staining type and pathogenicity. However, bacterial viability and contact with host cells is necessary, indicating that an active interaction between bacteria and the host is important. Furthermore, the strongest response is observed in cells originating from the natural site of the infection, suggesting that the EGR1 induction is cell type specific. Finally, we show that EGFR–ERK1/2 and β1-integrin signaling are the main pathways used for bacteria-mediated EGR1 upregulation. In conclusion, the increase of EGR1 expression in epithelial cells is a common stress induced, cell type specific response upon host-bacteria interaction that is mediated by EGFR–ERK1/2 and β1-integrin signaling.

A NOX2/Egr-1/Fyn pathway delineates new targets for TKI-resistant malignancies

Tyrosine kinase inhibitors (TKI) have improved CML response rates, and some are effective against resistance-promoting point mutations in BCR-ABL1. However, in the absence of point mutations, resistance still occurs. Here, we identify a novel pathway mediating resistance which connects p47phox, the organizer subunit of NADPH oxidase-2 (NOX2), with early growth response-1 (Egr-1) and the Src family kinase Fyn. We found up-regulation of p47phox, Egr-1, and Fyn mRNA and protein using paired isogenic CML cell lines and mined data. Isolation of CD34⁺ cells and tissue microarray staining from blast crisis CML patients confirmed in vivo over-expression of components of this pathway. Knockdown studies revealed that p47phox modulated reactive oxygen species and Egr-1 expression, which, in turn, controlled Fyn expression. Interestingly, Fyn knockdown sensitized TKI-resistant cells to dasatinib, a dual BCR-ABL1/Src inhibitor. Egr-1 knockdown had similar effects, indicating the utility of targeting Fyn expression over activation. Pointedly, p47phox knockdown also restored TKI-sensitivity, indicating that targeting the NOX2 complex can overcome resistance. The NOX2/Egr-1/Fyn pathway was also conserved within TKI-resistant EGFRΔIII-expressing glioblastoma and patient-derived glioblastoma stem cells. Thus, our findings suggest that targeting the NOX2/Egr-1/Fyn pathway may have clinical implications within multiple cancer types; particularly where efficacy of TKI is compromised.

Efficacy of a Cancer Vaccine against ALK-Rearranged Lung Tumors

Non-small cell lung cancer (NSCLC) harboring chromosomal rearrangements of the anaplastic lymphoma kinase (ALK) gene is treated with ALK tyrosine kinase inhibitors (TKI), but the treatment is successful for only a limited amount of time; most patients experience a relapse due to the development of drug resistance. Here, we show that a vaccine against ALK induced a strong and specific immune response that both prophylactically and therapeutically impaired the growth of ALK-positive lung tumors in mouse models. The ALK vaccine was efficacious also in combination with ALK TKI treatment and significantly delayed tumor relapses after TKI suspension. We found that lung tumors containing ALK rearrangements induced an immunosuppressive microenvironment, regulating the expression of PD-L1 on the surface of lung tumor cells. High PD-L1 expression reduced ALK vaccine efficacy, which could be restored by administration of anti-PD-1 immunotherapy. Thus, combinations of ALK vaccine with TKIs and immune checkpoint blockade therapies might represent a powerful strategy for the treatment of ALK-driven NSCLC.

Convergent mutations and kinase fusions lead to oncogenic STAT3 activation in anaplastic large cell lymphoma

A systematic characterization of the genetic alterations driving ALCLs has not been performed. By integrating massive sequencing strategies, we provide a comprehensive characterization of driver genetic alterations (somatic point mutations, copy number alterations, and gene fusions) in ALK(-) ALCLs. We identified activating mutations of JAK1 and/or STAT3 genes in ∼20% of 88 [corrected] ALK(-) ALCLs and demonstrated that 38% of systemic ALK(-) ALCLs displayed double lesions. Recurrent chimeras combining a transcription factor (NFkB2 or NCOR2) with a tyrosine kinase (ROS1 or TYK2) were also discovered in WT JAK1/STAT3 ALK(-) ALCL. All these aberrations lead to the constitutive activation of the JAK/STAT3 pathway, which was proved oncogenic. Consistently, JAK/STAT3 pathway inhibition impaired cell growth in vitro and in vivo.

A functional landscape of resistance to ALK inhibition in lung cancer

We conducted a large-scale functional genetic study to characterize mechanisms of resistance to ALK inhibition in ALK-dependent lung cancer cells. We identify members of known resistance pathways and additional putative resistance drivers. Among the latter were members of the P2Y purinergic receptor family of G-protein-coupled receptors (P2Y1, P2Y2, and P2Y6). P2Y receptors mediated resistance in part through a protein-kinase-C (PKC)-dependent mechanism. Moreover, PKC activation alone was sufficient to confer resistance to ALK inhibitors, whereas combined ALK and PKC inhibition restored sensitivity. We observed enrichment of gene signatures associated with several resistance drivers (including P2Y receptors) in crizotinib-resistant ALK-rearranged lung tumors compared to treatment-naive controls, supporting a role for these identified mechanisms in clinical ALK inhibitor resistance.

Activated MET acts as a salvage signal after treatment with alectinib, a selective ALK inhibitor, in ALK-positive non-small cell lung cancer

Non-small cell lung cancer (NSCLC) carrying echinoderm microtubule-associated protein-like 4 (EML4)-anaplastic lymphoma kinase (ALK) rearrangements is hypersensitive to ALK inhibitors, including crizotinib and alectinib. Crizotinib was initially designed as a MET inhibitor, whereas alectinib is a selective ALK inhibitor. The MET signal, which is inhibited by crizotinib but not by alectinib, is dysregulated in many human cancers. However, the role of the MET signal in ALK-positive NSCLC remains unclear. In this study, we found that hepatocyte growth factor (HGF), ligand of MET, mediated the resistance to alectinib, but not to crizotinib, via the MET signal in ALK-positive NSCLC cell lines (H3122 and H2228 cell lines). In addition, alectinib activated the MET signal even in the absence of HGF and the inhibition of the MET signal enhanced the efficacy of alectinib. These findings suggest that activated MET acts as a salvage signal in ALK-positive NSCLC. This novel role of the MET signal in ALK-positive NSCLC may pave the way for further clinical trials examining MET inhibitors.

ALK-dependent control of hypoxia-inducible factors mediates tumor growth and metastasis

Rearrangements involving the anaplastic lymphoma kinase (ALK) gene are defining events in several tumors, including anaplastic large-cell lymphoma (ALCL) and non-small cell lung carcinoma (NSCLC). In such cancers, the oncogenic activity of ALK stimulates signaling pathways that induce cell transformation and promote tumor growth. In search for common pathways activated by oncogenic ALK across different tumors types, we found that hypoxia pathways were significantly enriched in ALK-rearranged ALCL and NSCLC, as compared with other types of T-cell lymphoma or EGFR- and K-RAS-mutated NSCLC, respectively. Consistently, in both ALCL and NSCLC, we found that under hypoxic conditions, ALK directly regulated the abundance of hypoxia-inducible factors (HIF), which are key players of the hypoxia response in normal tissues and cancers. In ALCL, the upregulation of HIF1α and HIF2α in hypoxic conditions required ALK activity and its downstream signaling proteins STAT3 and C/EBPβ. In vivo, ALK regulated VEGFA production and tumor angiogenesis in ALCL and NSCLC, and the treatment with the anti-VEGFA antibody bevacizumab strongly impaired ALCL growth in mouse xenografts. Finally, HIF2α, but not HIF1α, was required for ALCL growth in vivo whereas the growth and metastasis potential of ALK-rearranged NSCLC required both HIF1α and HIF2α. In conclusion, we uncovered an ALK-specific regulation of the hypoxia response across different ALK(+) tumor types and propose HIFs as a powerful specific therapeutic target in ALK-rearranged ALCL and NSCLC.

Resistance to ROS1 inhibition mediated by EGFR pathway activation in non-small cell lung cancer

The targeting of oncogenic ‘driver’ kinases with small molecule inhibitors has proven to be a highly effective therapeutic strategy in selected non-small cell lung cancer (NSCLC) patients. However, acquired resistance to targeted therapies invariably arises and is a major limitation to patient care. ROS1 fusion proteins are a recently described class of oncogenic driver, and NSCLC patients that express these fusions generally respond well to ROS1-targeted therapy. In this study, we sought to determine mechanisms of acquired resistance to ROS1 inhibition. To accomplish this, we analyzed tumor samples from a patient who initially responded to the ROS1 inhibitor crizotinib but eventually developed acquired resistance. In addition, we generated a ROS1 inhibition-resistant derivative of the initially sensitive NSCLC cell line HCC78. Previously described mechanisms of acquired resistance to tyrosine kinase inhibitors including target kinase-domain mutation, target copy number gain, epithelial-mesenchymal transition, and conversion to small cell lung cancer histology were found to not underlie resistance in the patient sample or resistant cell line. However, we did observe a switch in the control of growth and survival signaling pathways from ROS1 to EGFR in the resistant cell line. As a result of this switch, ROS1 inhibition-resistant HCC78 cells became sensitive to EGFR inhibition, an effect that was enhanced by co-treatment with a ROS1 inhibitor. Our results suggest that co-inhibition of ROS1 and EGFR may be an effective strategy to combat resistance to targeted therapy in some ROS1 fusion-positive NSCLC patients.

Functional and pathway enrichment analysis for integrated regulatory network of high- and low-metastatic lung cancer

Metastasis is a common feature of lung cancer, involving relationships between genes, proteins and miRNAs. However, lack of early detection and limited options for targeted therapies are weaknesses that cantribute to the dismal statistics observed in lung cancer metastasis. In this paper, gene expression profiling analysis for genes differentially expressed between high- (95D) and low-metastatic lung cancer cell lines (95C) was performed using gene annotation, pathway analysis, literature mining, and the integrated regulatory network as well as motif analysis of miRNA-DEG and TF-DEG. In addition, the expression of EGR-1 (early growth reponse-1) in surgically resected lung squamous carcinomas, adenocarcinomas and normal lung tissue was detected by immunohistochemistry to reveal the relationships between EGR-1 and lung cancer metastasis. A total of 570 different expressed genes (DEGs) were screened, the vast majority of up-regulated DEGs were connected to cell adhesion and focal adhesion. EGR-1 was observed in the center node of the regulatory network, which seems to play a role in the process of cancer metastasis, and further immunohistochemistry detection confirmed this reasoning. Besides EGR-1, several significant module-related DEGs were enriched in the pathway within cancer and focal adhesion according to KEGG pathway enrichment analysis of network modules. The construction of an integrated regulatory network and the functional prediction of EGR-1 provided us with the cytological basis of lung cancer metastasis research and an understanding of the mechanism of metastasis in lung cancer. EGR-1 should be considered as a potential target gene in therapeutic agent for lung cancer metastasis.