Whole exome sequencing and MicroRNA profiling of lung adenocarcinoma identified risk prediction features for tumors at stage I and its substages.

OBJECTIVES: About 20% of stage I lung adenocarcinoma (LUAD) patients suffer a relapse after surgical resection. While finer substages have been defined and refined in the AJCC staging system, clinical investigations on the tumor molecular landscape are lacking. MATERIALS AND METHODS: We performed whole exome sequencing, DNA copy number and microRNA profiling on paired tumor-normal samples from a cohort of 113 treatment-naïve stage I Taiwanese LUAD patients. We searched for molecular features associated with relapse-free survival (RFS) of stage I or its substages and validated the findings with an independent Caucasian LUAD cohort. RESULTS: We found sixteen nonsynonymous mutations harbored at EGFR, KRAS, TP53, CTNNB1 and six other genes associated with poor RFS in a dose-dependent manner via variant allele fraction (VAF). An index, maxVAF, was constructed to quantify the overall mutation load from genes other than EGFR. High maxVAF scores discriminated a small group of high-risk LUAD at stage I (median RFS: 4.5 versus 69.5 months; HR = 10.5, 95% CI = 4.22-26.12, P < 0.001). At the substage level, higher risk was found for patients with high maxVAF or high miR-31; IA (median RFS: 32.1 versus 122.8 months, P = 0.005) and IB (median RFS: 7.1 versus 26.2, P = 0.049). MicroRNAs, miR-182, miR-183 and miR-196a were found correlated with EGFR mutation and poor RFS in stage IB patients. CONCLUSION: Distinctive features of somatic gene mutation and microRNA expression of stage I LUAD are characterized to complement the survival prognosis by substaging. The findings open up more options for precision management of stage I LUAD patients.

Association of Pathway Mutations With Survival in Taiwanese Breast Cancers.

Breast cancer is the most common invasive cancer in women worldwide. Next-generation sequencing (NGS) provides a high-resolution profile of cancer genome. Our study ultimately gives the insight for genetic screening to identify the minority of patients with breast cancer with a poor prognosis, who might benefit from the most intensive possible treatment. The detection of mutations can polish the traditional method to detect high-risk patients who experience poor prognosis, recurrence and death early. In total, 147 breast cancer tumors were sequenced with targeted sequencing using a RainDance Cancer Hotspot Panel. The average age of all 147 breast cancer patients in the study was 51.7 years, with a range of 21-77 years. The average sequencing depth was 5,222x (range 2,900x-8,633x), and the coverage was approximately 100%. A total of 235 variants in 43 genes were detected in 147 patients by high-depth Illumina sequencing. A total of 219 single nucleotide variations were found in 42 genes from 147 patients, and 16 indel mutations were found in 13 genes from 84 patients. After filtering with the 1000 Genomes database and for synonymous SNPs, we focused on 54 somatic functional point mutations. The functional point mutations contained 54 missense mutations in 22 genes. Additionally, mutation of genes within the RET, PTEN, CDH1, MAP2K4, NF1, ERBB2, RUNX1, PIK3CA, FGFR3, KIT, KDR, APC, SMO, NOTCH1, and FBXW7 in breast cancer patients were with poor prognosis. Moreover, TP53 and APC mutations were enriched in triple-negative breast cancer. APC mutations were associated with a poor prognosis in human breast cancer (log-rank P<0.001). Our study identified tumor mutation hotspot profiles in Taiwanese breast cancer patients, revealing new targetable gene mutations in Asian breast cancer patients.

Tumor microenvironment-based screening repurposes drugs targeting cancer stem cells and cancer-associated fibroblasts.

The tumorous niche may drive the plasticity of heterogeneity and cancer stemness, leading to drug resistance and metastasis, which is the main reason of treatment failure in most cancer patients. The aim of this study was to establish a tumor microenvironment (TME)-based screening to identify drugs that can specifically target cancer stem cells (CSCs) and cancer-associated fibroblasts (CAFs) in the TME. Methods: Lung cancer patient-derived cancer cell and CAFs were utilized to mimic the TME and reproduce the stemness properties of CSCs in vitro and develop a high-throughput drug screening platform with phenotypical parameters. Limiting dilution assay, sphere-forming and ALDH activity assay were utilized to measure the cancer stemness characteristics. In vivo patient-derived xenograft (PDX) models and single-cell RNA sequencing were used to evaluate the mechanisms of the compounds in CSCs and CAFs. Results: The TME-based drug screening platform could comprehensively evaluate the response of cancer cells, CSCs and CAFs to different treatments. Among the 1,524 compounds tested, several drugs were identified to have anti-CAFs, anticancer and anti-CSCs activities. Aloe-emodin and digoxin both show anticancer and anti-CSCs activity in vitro and in vivo, which was further confirmed in the lung cancer PDX model. The combination of digoxin and chemotherapy improved therapeutic efficacy. The single-cell transcriptomics analysis revealed that digoxin could suppress the CSCs subpopulation in CAFs-cocultured cancer cells and cytokine production in CAFs. Conclusions: The TME-based drug screening platform provides a tool to identify and repurpose compounds targeting cancer cells, CSCs and CAFs, which may accelerate drug development and therapeutic application for lung cancer patients.

DNA methylome and transcriptome landscapes of cancer-associated fibroblasts reveal a smoking-associated malignancy index.

Unlike the better-studied aberrant epigenome in the tumor, the clinicopathologic impact of DNA methylation in the tumor microenvironment (TME), especially the contribution from cancer-associated fibroblasts (CAFs), remains elusive. CAFs exhibit profound patient-to-patient tumorigenic heterogeneity. We asked whether such heterogeneity may be exploited to quantify the level of TME malignancy. We developed a robust and efficient methylome/transcriptome co-analytical system for CAFs and paired normal fibroblasts (NFs) from non-small-cell lung cancer patients. We found 14,781 CpG sites of CAF/NF differential methylation, of which 3,707 sites showed higher methylation changes in ever-smokers than in nonsmokers. Concomitant CAF/NF differential gene expression analysis pointed to a subset of 54 smoking-associated CpG sites with strong methylation-regulated gene expression. A methylation index that summarizes the ß values of these CpGs was built for NF/CAF discrimination (MIND) with high sensitivity and specificity. The potential of MIND in detecting premalignancy across individual patients was shown. MIND succeeded in predicting tumor recurrence in multiple lung cancer cohorts without reliance on patient survival data, suggesting that the malignancy level of TME may be effectively graded by this index. Precision TME grading may provide additional pathological information to guide cancer prognosis and open up more options in personalized medicine.

Genome-Wide Epigenetic Landscape of Lung Adenocarcinoma Links HOXB9 DNA Methylation to Intrinsic EGFR-TKI Resistance and Heterogeneous Responses.

PURPOSE: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs. PATIENTS AND METHODS: We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations. RESULTS: A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox (HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019). CONCLUSION: Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

The M1/M2 spectrum and plasticity of malignant pleural effusion-macrophage in advanced lung cancer.

BACKGROUND: Malignant pleural effusion (MPE)-macrophage (Mφ) of lung cancer patients within unique M1/M2 spectrum showed plasticity in M1-M2 transition. The M1/M2 features of MPE-Mφ and their significance to patient outcomes need to be clarified; furthermore, whether M1-repolarization could benefit treatment remains unclear. METHODS: Total 147 stage-IV lung adenocarcinoma patients undergoing MPE drainage were enrolled for profiling and validation of their M1/M2 spectrum. In addition, the MPE-Mφ signature on overall patient survival was analyzed. The impact of the M1-polarization strategy of patient-derived MPE-Mφ on anti-cancer activity was examined. RESULTS: We found that MPE-Mφ expressed both traditional M1 (HLA-DRA) and M2 (CD163) markers and showed a wide range of M1/M2 spectrum. Most of the MPE-Mφ displayed diverse PD-L1 expression patterns, while the low PD-L1 expression group was correlated with higher levels of IL-10. Among these markers, we identified a novel two-gene MPE-Mφ signature, IL-1ß and TGF-ß1, representing the M1/M2 tendency, which showed a strong predictive power in patient outcomes in our MPE-Mφ patient cohort (N = 60, p = 0.013) and The Cancer Genome Atlas Lung Adenocarcinoma dataset (N = 478, p < 0.0001). Significantly, ß-glucan worked synergistically with IFN-γ to reverse the risk signature by repolarizing the MPE-Mφ toward the M1 pattern, enhancing anti-cancer activity. CONCLUSIONS: We identified MPE-Mφ on the M1/M2 spectrum and plasticity and described a two-gene M1/M2 signature that could predict the outcome of late-stage lung cancer patients. In addition, we found that "re-education" of these MPE-Mφ toward anti-cancer M1 macrophages using clinically applicable strategies may overcome tumor immune escape and benefit anti-cancer therapies.

Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93-28.32, p < 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.

Tumor mutation burden and recurrent tumors in hereditary lung cancer.

Lung cancer is the leading cause of cancer death worldwide and cancer relapse accounts for the majority of cancer mortality. The mechanism is still unknown, especially in hereditary lung cancer without known actionable mutations. To identify genetic alternations involved in hereditary lung cancer and relapse is urgently needed. We collected genetic materials from a unique hereditary lung cancer patient's blood, first cancer tissue (T1), adjacent normal tissue (N1), relapse cancer tissue (T2), and adjacent normal tissue (N2) for whole genome sequencing. We identified specific mutations in T1 and T2, and attributed them to tumorigenesis and recurrence. These tumor specific variants were enriched in antigen presentation pathway. In addition, a lung adenocarcinoma cohort from the TCGA dataset was used to confirm our findings. Patients with high mutation burdens in tumor specific genes had decreased relapse-free survival (P = 0.017, n = 186). Our study may provide important insight for designing immunotherapeutic treatment for hereditary lung cancer.

Genome-Wide Scan for Copy Number Alteration Association with Relapse-Free Survival in Colorectal Cancer with Liver Metastasis Patients.

Predicting a patient's risk of recurrence after the resection of liver metastases from colorectal cancer is critical for evaluating and selecting therapeutic approaches. Clinical and pathologic parameters have shown limited accuracy thus far. Therefore, we combined the clinical status with a genomic approach to stratify relapse-free survival in colorectal cancer liver metastases patients. To identify new molecular and genetic signatures specific to colorectal cancer with liver metastasis (CRCLM) patients, we conducted DNA copy number profiling on a cohort of 21 Taiwanese CRCLM patients using a comparative genomic hybridization (CGH) array. We identified a three-gene signature based on differential copy number alteration between patients with different statuses of (1) recurrence and (2) synchronous metastasis. In relapse hotspot regions, only three genes (S100PBP, CSMD2, and TGFBI) were significantly associated with the synchronous liver metastasis factor. A final set of three genes-S100PBP, CSMD2, TGFBI-significantly predicted relapse-free survival in our cohort (p = 0.04) and another CRCLM cohort (p = 0.02). This three-gene signature is the first genomic signature validated for relapse-free survival in post-hepatectomy CRCLM patients. Our three-gene signature was developed using a whole-genome CGH array and has a good prognostic position for the relapse-free survival of CRCLM patients after hepatectomy.

ePIANNO: ePIgenomics ANNOtation tool.

Recently, with the development of next generation sequencing (NGS), the combination of chromatin immunoprecipitation (ChIP) and NGS, namely ChIP-seq, has become a powerful technique to capture potential genomic binding sites of regulatory factors, histone modifications and chromatin accessible regions. For most researchers, additional information including genomic variations on the TF binding site, allele frequency of variation between different populations, variation associated disease, and other neighbour TF binding sites are essential to generate a proper hypothesis or a meaningful conclusion. Many ChIP-seq datasets had been deposited on the public domain to help researchers make new discoveries. However, researches are often intimidated by the complexity of data structure and largeness of data volume. Such information would be more useful if they could be combined or downloaded with ChIP-seq data. To meet such demands, we built a webtool: ePIgenomic ANNOtation tool (ePIANNO, http://epianno.stat.sinica.edu.tw/index.html). ePIANNO is a web server that combines SNP information of populations (1000 Genomes Project) and gene-disease association information of GWAS (NHGRI) with ChIP-seq (hmChIP, ENCODE, and ROADMAP epigenomics) data. ePIANNO has a user-friendly website interface allowing researchers to explore, navigate, and extract data quickly. We use two examples to demonstrate how users could use functions of ePIANNO webserver to explore useful information about TF related genomic variants. Users could use our query functions to search target regions, transcription factors, or annotations. ePIANNO may help users to generate hypothesis or explore potential biological functions for their studies.

EGFR-activating mutations, DNA copy number abundance of ErbB family, and prognosis in lung adenocarcinoma.

In this study, EGFR-activating mutation status and DNA copy number abundances of members of ErbB family were measured in 261 lung adenocarcinomas. The associations between DNA copy number abundances of ErbB family, EGFR-activating mutation status, and prognosis were explored. Results showed that DNA copy number abundances of EGFR, ERBB2, ERBB3, and ERBB4 had associations with overall survival in lung adenocarcinoma with EGFR-activating mutations. In the stratification analysis, only ERBB2 showed significant discrepancy in patients carrying wild type EGFR and other members of ErbB family in patients carrying EGFR-activating mutation. This indicated that CNAs of ErbB family had effect modifications of EGFR-activating mutation status. Findings of this study demonstrate potential molecular guidance of patient management of lung adenocarcinoma with or without EGFR-activating mutations.

Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain.

Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary, and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior, and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development.

A comparison of isolated circulating tumor cells and tissue biopsies using whole-genome sequencing in prostate cancer.

Previous studies have demonstrated focal but limited molecular similarities between circulating tumor cells (CTCs) and biopsies using isolated genetic assays. We hypothesized that molecular similarity between CTCs and tissue exists at the single cell level when characterized by whole genome sequencing (WGS). By combining the NanoVelcro CTC Chip with laser capture microdissection (LCM), we developed a platform for single-CTC WGS. We performed this procedure on CTCs and tissue samples from a patient with advanced prostate cancer who had serial biopsies over the course of his clinical history. We achieved 30X depth and ≥ 95% coverage. Twenty-nine percent of the somatic single nucleotide variations (SSNVs) identified were founder mutations that were also identified in CTCs. In addition, 86% of the clonal mutations identified in CTCs could be traced back to either the primary or metastatic tumors. In this patient, we identified structural variations (SVs) including an intrachromosomal rearrangement in chr3 and an interchromosomal rearrangement between chr13 and chr15. These rearrangements were shared between tumor tissues and CTCs. At the same time, highly heterogeneous short structural variants were discovered in PTEN, RB1, and BRCA2 in all tumor and CTC samples. Using high-quality WGS on single-CTCs, we identified the shared genomic alterations between CTCs and tumor tissues. This approach yielded insight into the heterogeneity of the mutational landscape of SSNVs and SVs. It may be possible to use this approach to study heterogeneity and characterize the biological evolution of a cancer during the course of its natural history.

R331W Missense Mutation of Oncogene YAP1 Is a Germline Risk Allele for Lung Adenocarcinoma With Medical Actionability.

PURPOSE: Adenocarcinoma is the most dominant type of lung cancer in never-smoker patients. The risk alleles from genome-wide association studies have small odds ratios and unclear biologic roles. Here we have taken an approach featuring suitable medical actionability to identify alleles with low population frequency but high disease-causing potential. PATIENTS AND METHODS: Whole-genome sequencing was performed for a family with an unusually high density of lung adenocarcinoma with available DNA from the affected mother, four affected daughters, and one nonaffected son. Candidate risk alleles were confirmed by matrix-assisted laser desorption ionization time of flight mass spectroscopy. Validation was conducted in an external cohort of 1,135 participants without cancer and 1,312 patients with lung adenocarcinoma. Family follow-ups were performed by genotyping the relatives of the original proband and the relatives of the identified risk-allele carriers. Low-dose computed tomography scans of the chest were evaluated for lung abnormalities. RESULTS: YAP1 R331W missense mutation from the original family was identified and validated in the external controls and the cohort with lung adenocarcinoma. The YAP1 mutant-allele carrier frequency was 1.1% in patients with lung adenocarcinoma compared with 0.18% in controls (P = .0095), yielding an odds ratio (adjusted for age, sex, and smoking status) of 5.9. Among the relatives, YAP1-mutant carriers have overwhelmingly higher frequencies of developing lung adenocarcinoma or ground-glass opacity lung lesions than those who do not carry the mutation (10:0 v 1:7; P < .001). YAP1 mutation was shown to increase the colony formation ability and invasion potential of lung cancer cells. CONCLUSION: These results implicated YAP1 R331W as an allele predisposed for lung adenocarcinoma with high familial penetrance. Low-dose computed tomography scans may be recommended to this subpopulation, which is at high risk for lung cancer, for personalized prevention and health management.

Subclassification of prostate cancer circulating tumor cells by nuclear size reveals very small nuclear circulating tumor cells in patients with visceral metastases.

BACKGROUND: Although enumeration of circulating tumor cells (CTCs) has shown some clinical value, the pool of CTCs contains a mixture of cells that contains additional information that can be extracted. The authors subclassified CTCs by shape features focusing on nuclear size and related this with clinical information. METHODS: A total of 148 blood samples were obtained from 57 patients with prostate cancer across the spectrum of metastatic states: no metastasis, nonvisceral metastasis, and visceral metastasis. CTCs captured and enumerated on NanoVelcro Chips (CytoLumina, Los Angeles, Calif) were subjected to pathologic review including nuclear size. The distribution of nuclear size was analyzed using a Gaussian mixture model. Correlations were made between CTC subpopulations and metastatic status. RESULTS: Statistical modeling of nuclear size distribution revealed 3 distinct subpopulations: large nuclear CTCs, small nuclear CTCs, and very small nuclear CTCs (vsnCTCs). Small nuclear CTCs and vsnCTC identified those patients with metastatic disease. However, vsnCTC counts alone were found to be elevated in patients with visceral metastases when compared with those without (0.36 ± 0.69 vs 1.95 ± 3.77 cells/mL blood; P<.001). Serial enumeration studies suggested the emergence of vsnCTCs occurred before the detection of visceral metastases. CONCLUSIONS: There are morphologic subsets of CTCs that can be identified by fundamental pathologic approaches, such as nuclear size measurement. The results of this observational study strongly suggest that CTCs contain relevant information regarding disease status. In particular, the detection of vsnCTCs was found to be correlated with the presence of visceral metastases and should be formally explored as a putative blood-borne biomarker to identify patients at risk of developing this clinical evolution of prostate cancer.

Cancer-associated fibroblasts regulate the plasticity of lung cancer stemness via paracrine signalling.

Cancer stem cells (CSCs) are a promising target for treating cancer, yet how CSC plasticity is maintained in vivo is unclear and is difficult to study in vitro. Here we establish a sustainable primary culture of Oct3/4(+)/Nanog(+) lung CSCs fed with CD90(+) cancer-associated fibroblasts (CAFs) to further advance our knowledge of preserving stem cells in the tumour microenvironment. Using transcriptomics we identify the paracrine network by which CAFs enrich CSCs through de-differentiation and reacquisition of stem cell-like properties. Specifically, we find that IGF1R signalling activation in cancer cells in the presence of CAFs expressing IGF-II can induce Nanog expression and promote stemness. Moreover, this paracrine signalling predicts overall and relapse-free survival in stage I non-small cell lung cancer (NSCLC) patients. IGF-II/IGF1R signalling blockade inhibits Nanog expression and attenuates cancer stem cell features. Our data demonstrate that CAFs constitute a supporting niche for cancer stemness, and targeting this paracrine signalling may present a new therapeutic strategy for NSCLC.

Focal amplification of HOXD-harboring chromosome region is implicated in multiple-walled carbon nanotubes-induced carcinogenicity.

Multiple-walled carbon nanotubes (MWCNTs) may cause carcinogenesis. We found that long-term exposure to MWCNTs can induce irreversible oncogenic transformation of human bronchial epithelial cells and tumorigenicity in vivo. A genome-wide array-comparative genomic hybridization (aCGH) analysis revealed global chromosomal aberration in MWCNTs-treated clones, predominantly at chromosome 2q31-32, where the potential oncogenes HOXD9 and HOXD13 are located. Functional assays confirmed that this variation can modulate oncogenic signaling and plays a part in MWCNTs-induced tumorigenesis, suggesting that MWCNTs are carcinogens that act by altering genomic stability and oncogenic copy numbers.

Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity.

BACKGROUND: Chemosensitivity and tumor metastasis are two primary issues in cancer management. Cancer cells often exhibit a wide range of sensitivity to anti-cancer compounds. To gain insight on the genetic mechanism of drug sensitivity, one powerful approach is to employ the panel of 60 human cancer cell lines developed by the National Cancer Institute (NCI). Cancer cells also show a broad range of invasion ability. However, a genome-wide portrait on the contributing molecular factors to invasion heterogeneity is lacking. METHODS: Our lab performed an invasion assay on the NCI-60 panel. We identified invasion-associated (IA) genes by correlating our invasion profiling data with the Affymetrix gene expression data on NCI-60. We then employed the recently released chemosensitivity data of 99 anti-cancer drugs of known mechanism to investigate the gene-drug correlation, focusing on the IA genes. Afterwards, we collected data from four independent drug-testing experiments to validate our findings on compound response prediction. Finally, we obtained published clinical and molecular data from two recent adjuvant chemotherapy cohorts, one on lung cancer and one on breast cancer, to test the performance of our gene signature for patient outcome prediction. RESULTS: First, we found 633 IA genes from the invasion-gene expression correlation study. Then, for each of the 99 drugs, we obtained a subset of IA genes whose expression levels correlated with drug-sensitivity profiles. We identified a set of eight genes (EGFR, ITGA3, MYLK, RAI14, AHNAK, GLS, IL32 and NNMT) showing significant gene-drug correlation with paclitaxel, docetaxel, erlotinib, everolimus and dasatinib. This eight-gene signature (derived from NCI-60) for chemosensitivity prediction was validated by a total of 107 independent drug tests on 78 tumor cell lines, most of which were outside of the NCI-60 panel. The eight-gene signature predicted relapse-free survival for the lung and breast cancer patients (log-rank P = 0.0263; 0.00021). Multivariate Cox regression yielded a hazard ratio of our signature of 5.33 (95% CI = 1.76 to 16.1) and 1.81 (95% CI = 1.19 to 2.76) respectively. The eight-gene signature features the cancer hallmark epidermal growth factor receptor (EGFR) and genes involved in cell adhesion, migration, invasion, tumor growth and progression. CONCLUSIONS: Our study sheds light on the intricate three-way interplay among gene expression, invasion and compound-sensitivity. We report the finding of a unique signature that predicts chemotherapy survival for both lung and breast cancer. Augmenting the NCI-60 model with in vitro characterization of important phenotype-like invasion potential is a cost-effective approach to power the genomic chemosensitivity analysis.

α-Catulin drives metastasis by activating ILK and driving an αvß3 integrin signaling axis.

α-Catulin is an oncoprotein that helps sustain proliferation by preventing cellular senescence. Here, we report that α-catulin also drives malignant invasion and metastasis. α-Catulin was upregulated in highly invasive non-small cell lung cancer (NSCLC) cell lines, where its ectopic expression or short-hairpin RNA-mediated attenuation enhanced or limited invasion or metastasis, respectively. α-Catulin interacted with integrin-linked kinase (ILK), a serine/threonine protein kinase implicated in cancer cell proliferation, antiapoptosis, invasion, and angiogenesis. Attenuation of ILK or α-catulin reciprocally blocked cell migration and invasion induced by the other protein. Mechanistic investigations revealed that α-catulin activated Akt-NF-κB signaling downstream of ILK, which in turn led to increased expression of fibronectin and integrin αvß3. Pharmacologic or antibody-mediated blockade of NF-κB or αvß3 was sufficient to inhibit α-catulin-induced cell migration and invasion. Clinically, high levels of expression of α-catulin and ILK were associated with poor overall survival in patients with NSCLC. Taken together, our study shows that α-catulin plays a critical role in cancer metastasis by activating the ILK-mediated Akt-NF-κB-αvß3 signaling axis.

Human protein-protein interaction prediction by a novel sequence-based co-evolution method: co-evolutionary divergence.

MOTIVATION: Protein-protein interaction (PPI) plays an important role in understanding gene functions, and many computational PPI prediction methods have been proposed in recent years. Despite the extensive efforts, PPI prediction still has much room to improve. Sequence-based co-evolution methods include the substitution rate method and the mirror tree method, which compare sequence substitution rates and topological similarity of phylogenetic trees, respectively. Although they have been used to predict PPI in species with small genomes like Escherichia coli, such methods have not been tested in large scale proteome like Homo sapiens. RESULT: In this study, we propose a novel sequence-based co-evolution method, co-evolutionary divergence (CD), for human PPI prediction. Built on the basic assumption that protein pairs with similar substitution rates are likely to interact with each other, the CD method converts the evolutionary information from 14 species of vertebrates into likelihood ratios and combined them together to infer PPI. We showed that the CD method outperformed the mirror tree method in three independent human PPI datasets by a large margin. With the arrival of more species genome information generated by next generation sequencing, the performance of the CD method can be further improved. AVAILABILITY: Source code and support are available at http://mib.stat.sinica.edu.tw/LAP/tmp/CD.rar.