Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer

A discrimination index for selecting markers of tumor growth dynamic across multiple cancer studies with a cure fraction

To identify genomic markers with consistent effect on tumor dynamics across multiple cancer series, discrimination indices based on proportional hazards models can be used since they do not depend heavily on the sample size. However, the underlying assumption of proportionality of the hazards does not always hold, especially when the studied population is a mixture of cured and uncured patients, like in early-stage cancers. We propose a novel index that quantifies the capability of a genomic marker to separate uncured patients, according to their time-to-event outcomes. It allows to identify genomic markers characterizing tumor growth dynamic across multiple studies. Simulation results show that our index performs better than classical indices based on the Cox model. It is neither affected by the sample size nor the cure rate fraction. In a cross-study of early-stage breast cancers, the index allows to select genomic markers with a potential consistent effect on tumor growth dynamics.

cAMP responsive element binding protein-1 is a transcription factor of lysosomal-associated protein transmembrane-4 Beta in human breast cancer cells

Lysosomal-associated protein transmembrane-4 beta (LAPTM4B) is a potential proto-oncogene, whose overexpression is involved in cancer occurrence and progression. Its transcript is up-regulated in various types of solid tumors including breast cancer. However, its transcriptional regulation mechanism is still unclear. To investigate the mechanism of transcriptional regulation of LAPTM4B in human breast cancer cells, a series of luciferase reporter constructs and construct with mutated binding site for cAMP responsive element binding protein-1 (CREB1) were generated by PCR amplification and transiently transfected into breast cancer cells to determine the transcriptional activities of different promoter regions. The +10+292 promoter region was possessed the highest transcriptional activity. The ability of CREB1 to bind the LAPMT4B promoter was confirmed by electrophoretic mobility shift assay, super-shift and RNA interference experiments. Our study identified the core promoter region responsible for constitutive expression of LAPTM4B and clarified that CREB1 played an important role in LAPTM4B transcriptional regulation in human breast cancer cells.

Overexpression of YWHAZ relates to tumor cell proliferation and malignant outcome of gastric carcinoma

BACKGROUND

Several studies have demonstrated that YWHAZ (14-3-3ζ), included in the 14-3-3 family of proteins, has been implicated in the initiation and progression of cancers. We tested whether YWHAZ acted as a cancer-promoting gene through its activation/overexpression in gastric cancer (GC).

METHODS

We analysed 7 GC cell lines and 141 primary tumours, which were curatively resected in our hospital between 2001 and 2003.

RESULTS

Overexpression of the YWHAZ protein was frequently detected in GC cell lines (six out of seven lines, 85.7%) and primary tumour samples of GC (72 out of 141 cases, 51%), and significantly correlated with larger tumour size, venous and lymphatic invasion, deeper tumour depth, and higher pathological stage and recurrence rate. Patients with YWHAZ-overexpressing tumours had worse overall survival rates than those with non-expressing tumours in both intensity and proportion expression-dependent manner. YWHAZ positivity was independently associated with a worse outcome in multivariate analysis (P=0.0491, hazard ratio 2.3 (1.003-5.304)). Knockdown of YWHAZ expression using several specific siRNAs inhibited the proliferation, migration, and invasion of YWHAZ-overexpressing GC cells. Higher expression of the YWHAZ protein was significantly associated with the lower expression of miR-375 in primary GC tissues (P=0.0047).

CONCLUSION

These findings suggest that YWHAZ has a pivotal role in tumour cell proliferation through its overexpression, and highlight its usefulness as a prognostic factor and potential therapeutic target in GC.

Bridging cancer biology with the clinic: relative expression of a GRHL2-mediated gene-set pair predicts breast cancer metastasis

Identification and characterization of crucial gene target(s) that will allow focused therapeutics development remains a challenge. We have interrogated the putative therapeutic targets associated with the transcription factor Grainy head-like 2 (GRHL2), a critical epithelial regulatory factor. We demonstrate the possibility to define the molecular functions of critical genes in terms of their personalized expression profiles, allowing appropriate functional conclusions to be derived. A novel methodology, relative expression analysis with gene-set pairs (RXA-GSP), is designed to explore the potential clinical utility of cancer-biology discovery. Observing that Grhl2-overexpression leads to increased metastatic potential in vitro, we established a model assuming Grhl2-induced or -inhibited genes confer poor or favorable prognosis respectively for cancer metastasis. Training on public gene expression profiles of 995 breast cancer patients, this method prioritized one gene-set pair (GRHL2, CDH2, FN1, CITED2, MKI67 versus CTNNB1 and CTNNA3) from all 2717 possible gene-set pairs (GSPs). The identified GSP significantly dichotomized 295 independent patients for metastasis-free survival (log-rank tested p = 0.002; severe empirical p = 0.035). It also showed evidence of clinical prognostication in another independent 388 patients collected from three studies (log-rank tested p = 3.3e–6). This GSP is independent of most traditional prognostic indicators, and is only significantly associated with the histological grade of breast cancer (p = 0.0017), a GRHL2-associated clinical character (p = 6.8e–6, Spearman correlation), suggesting that this GSP is reflective of GRHL2-mediated events. Furthermore, a literature review indicates the therapeutic potential of the identified genes. This research demonstrates a novel strategy to integrate both biological experiments and clinical gene expression profiles for extracting and elucidating the genomic impact of a novel factor, GRHL2, and its associated gene-sets on the breast cancer prognosis. Importantly, the RXA-GSP method helps to individualize breast cancer treatment. It also has the potential to contribute considerably to basic biological investigation, clinical tools, and potential therapeutic targets.

Molecular characterization of basal-like and non-basal-like triple-negative breast cancer

Triple-negative (TN) and basal-like (BL) breast cancer definitions have been used interchangeably to identify breast cancers that lack expression of the hormone receptors and overexpression and/or amplification of HER2. However, both classifications show substantial discordance rates when compared to each other. Here, we molecularly characterize TN tumors and BL tumors, comparing and contrasting the results in terms of common patterns and distinct patterns for each. In total, when testing 412 TN and 473 BL tumors, 21.4% and 31.5% were identified as non-BL and non-TN, respectively. TN tumors identified as luminal or HER2-enriched (HER2E) showed undistinguishable overall gene expression profiles when compared versus luminal or HER2E tumors that were not TN. Similar findings were observed within BL tumors regardless of their TN status, which suggests that molecular subtype is preserved regardless of individual marker results. Interestingly, most TN tumors identified as HER2E showed low HER2 expression and lacked HER2 amplification, despite the similar overall gene expression profiles to HER2E tumors that were clinically HER2-positive. Lastly, additional genomic classifications were examined within TN and BL cancers, most of which were highly concordant with tumor intrinsic subtype. These results suggest that future clinical trials focused on TN disease should consider stratifying patients based upon BL versus non-BL gene expression profiles, which appears to be the main biological difference seen in patients with TN breast cancer.

LAPTM4B gene polymorphism and endometrial carcinoma risk and prognosis

A novel gene called LAPTM4B (lysosome-associated protein transmembrane 4 beta) plays several crucial roles in carcinogenesis. In this case-control study, we investigated the relationship between LAPTM4B gene polymorphism and susceptibility to endometrial carcinoma (EC). In an adjusted multivariate logistic regression analyses, subjects with the LAPTM4B*1/2 and *2/2 genotypes respectively exhibited 1.572-fold (95% confidence interval (CI) = 1.041-2.375) and 2.335-fold (95% CI = 1.365-3.995) increases in the risk of developing EC relative to those carrying LAPTM4B*1/1. Patients with LAPTM4B *2 had both significantly shorter overall survival (OS) and shorter disease-free survival (DFS) (both p < 0.001). Multivariate analysis showed that LAPTM4B genotype is an independent prognostic factor for OS and DFS (both p < 0.001). These results suggest that LAPTM4B polymorphisms might play an important role in the aetiology of EC.

Overexpression of LAPTM4B: an independent prognostic marker in breast cancer

PURPOSE

Lysosome-associated protein transmembrane 4 beta (LAPTM4B), a novel oncoprotein, has been shown to be overexpressed in several human malignancies. Our purpose was to evaluate the expression of LAPTM4B in breast carcinoma and its significance, which was not previously studied by others.

METHODS

Through immunohistochemistry, LAPTM4B expression was evaluated in 35 benign breast tumor specimens and 194 breast cancer specimens. The correlation of LAPTM4B expression with clinicopathological parameters was assessed using χ(2) analysis. The survival status of patients was analyzed using the Kaplan-Meier and log-rank tests. Cox regression was used for the multivariate analysis of prognostic factors.

RESULTS

The immunohistochemistry results showed that the expression level of LAPTM4B in breast cancer cases was significantly higher than that in benign breast tumor tissues (P < 0.001). Moreover, statistical analysis also showed that high LAPTM4B expression was positively related to TNM stage, lymph node metastasis, and recurrence. Furthermore, it was also shown that patients with high LAPTM4B expression had significantly poorer overall survival and disease-free survival compared with patients with low expression of LAPTM4B (P = 0.019 and P = 0.005, respectively). Multivariate Cox regression analysis revealed that high LAPTM4B expression level was an independent prognostic factor for both overall survival and disease-free survival of patients with breast cancer (P = 0.041 and P = 0.023, respectively).

CONCLUSIONS

Overexpression of LAPTM4B may contribute to the tumor progression and poor prognosis of breast cancer, thus testing the expression of LAPTM4B will be helpful for predicting prognosis in breast cancer.

PAR-5 is a PARty hub in the germline: Multitask proteins in development and disease

As our understanding of how molecular machineries work expands, an increasing number of proteins that appear as regulators of different processes have been identified. These proteins are hubs within and among functional networks. The 14-3-3 protein family is involved in multiple cellular pathways and, therefore, influences signaling in several disease processes, from neurobiological disorders to cancer. As a consequence, 14-3-3 proteins are currently being investigated as therapeutic targets. Moreover, 14-3-3 protein levels have been associated with resistance to chemotherapies. There are seven 14-3-3 genes in humans, while Caenorhabditis elegans only possesses two, namely par-5 and ftt-2. Among the C. elegans scientific community, par-5 is mainly recognized as one of the par genes that is essential for the asymmetric first cell division in the embryo. However, a recent study from our laboratory describes roles of par-5 in germ cell proliferation and in the cellular response to DNA damage induced by genotoxic agents. In this review, we explore the broad functionality of 14-3-3 proteins in C. elegans and comment on the potential use of worms for launching a drugs/modifiers discovery platform for the therapeutic regulation of 14-3-3 function in cancer.

14-3-3ζ as a predictor of early time to recurrence and distant metastasis in hormone receptor-positive and -negative breast cancers

The 14-3-3ζ gene, on 8q22, is often amplified in breast cancer and encodes a survival factor that interacts with and stabilizes many key signaling proteins. We examined the relationship between the expression of 14-3-3ζ, estrogen receptor α (ERα), and other parameters ( tumor size, grade, nodal status, progesterone receptor, HER2, EGFR, and p53) in matched primary and recurrence tumor tissue and how these factors impact time to recurrence, properties of the recurred tumors, and site of metastasis. In this cohort of over 100 patients, median time to recurrence was 3 years (range 1-17 years). Our analyses of primary tumor microarray cores revealed that 14-3-3ζ status was significantly correlated with tumor grade, size, and ERα. Women with 14-3-3ζ-positive and ERα-negative tumors had the earliest time to recurrence (median 1 yr, p < 0.001, hazard ratio 2.89), while median time to recurrence was 7 years for 14-3-3ζ-negative and ER-positive tumors. Of recurred tumors, 70-75 % were positive for 14-3-3ζ, up from the 45 % positivity of primary tumors. High expression of 14-3-3ζ also correlated with site of recurrence and showed a propensity for distant metastases to lung and chest wall. Multifactor correlation regression analysis revealed 14-3-3ζ to be a non-redundant, independent variable that adds clinical strength in predicting risk for early recurrence in ER-positive and -negative breast cancers, providing information beyond that of all other clinical pathological features examined. Thus, high expression of 14-3-3ζ in the primary tumor was significantly associated with earlier time to recurrence and with distant metastasis. Furthermore, even when the primary breast cancers were negative-low for 14-3-3ζ, the majority acquired increased expression in the recurrence. The findings underscore the detrimental role played by 14-3-3ζ in tumor aggressiveness and suggest that reducing its expression or interfering with its actions might substantially improve the clinical outcome for breast cancer patients.

Immunogenic cell death and DAMPs in cancer therapy

Although it was thought that apoptotic cells, when rapidly phagocytosed, underwent a silent death that did not trigger an immune response, in recent years a new concept of immunogenic cell death (ICD) has emerged. The immunogenic characteristics of ICD are mainly mediated by damage-associated molecular patterns (DAMPs), which include surface-exposed calreticulin (CRT), secreted ATP and released high mobility group protein B1 (HMGB1). Most DAMPs can be recognized by pattern recognition receptors (PRRs). In this Review, we discuss the role of endoplasmic reticulum (ER) stress and reactive oxygen species (ROS) in regulating the immunogenicity of dying cancer cells and the effect of therapy-resistant cancer microevolution on ICD.

SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B are markers of resistance to neoadjuvant chemotherapy in HER2-negative breast cancer

Response rates to chemotherapy remain highly variable in breast cancer patients. We set out to identify genes associated with chemotherapy resistance. We analyzed what is currently the largest single-institute set of gene expression profiles derived from breast cancers prior to a single neoadjuvant chemotherapy regimen (dose-dense doxorubicin and cyclophosphamide). We collected, gene expression-profiled, and analyzed 178 HER2-negative breast tumor biopsies ("NKI dataset"). We employed a recently developed approach for detecting imbalanced differential signal (DIDS) to identify markers of resistance to treatment. In contrast to traditional methods, DIDS is able to identify markers that show aberrant expression in only a small subgroup of the non-responder samples. We found a number of markers of resistance to anthracycline-based chemotherapy. We validated our findings in three external datasets, totaling 456 HER2-negative samples. Since these external sets included patients who received differing treatment regimens, the validated markers represent markers of general chemotherapy resistance. There was a highly significant overlap in the markers identified in the NKI dataset and the other three datasets. Five resistance markers, SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B, were identified in three of the four datasets (p value overlap < 1 × 10(-6)). These five genes identified resistant tumors that could not have been identified by merely taking ER status or proliferation into account. The identification of these genes might lead to a better understanding of the mechanisms involved in (clinically) observed chemotherapy resistance and could possibly assist in the recognition of breast cancers in which chemotherapy does not contribute to response or survival.

Cellular heterogeneity and molecular evolution in cancer

Intratumor heterogeneity represents a major obstacle to effective cancer treatment and personalized medicine. However, investigators are now elucidating intratumor heterogeneity at the single-cell level due to improvements in technologies. Better understanding of the composition of tumors, and monitoring changes in cell populations during disease progression and treatment, will improve cancer diagnosis and therapeutic design. Measurements of intratumor heterogeneity may also be used as biomarkers to predict the risk of progression and therapeutic resistance. We summarize important considerations related to intratumor heterogeneity during tumor evolution. We also discuss experimental approaches that are commonly used to infer intratumor heterogeneity and describe how these methodologies can be translated into clinical practice.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

Profiles of genomic instability in high-grade serous ovarian cancer predict treatment outcome

PURPOSE

High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR causes uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers.

EXPERIMENTAL DESIGN

We examined LOH and copy number changes using single nucleotide polymorphism array data from three HGSC cohorts and compared results to a cohort of high-grade breast cancers. The LOH profiles in HGSC were matched to chemotherapy resistance and progression-free survival (PFS).

RESULTS

LOH-based clustering divided HGSC into two clusters. The major group displayed extensive LOH and was further divided into two subgroups. The second group contained remarkably less LOH. BRCA1 promoter methylation was associated with the major group. LOH clusters were reproducible when validated in two independent HGSC datasets. LOH burden in the major cluster of HGSC was similar to triple-negative, and distinct from other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS.

CONCLUSIONS

Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors.

Met kinetic signature derived from the response to HGF/SF in a cellular model predicts breast cancer patient survival

To determine the signaling pathways leading from Met activation to metastasis and poor prognosis, we measured the kinetic gene alterations in breast cancer cell lines in response to HGF/SF. Using a network inference tool we analyzed the putative protein-protein interaction pathways leading from Met to these genes and studied their specificity to Met and prognostic potential. We identified a Met kinetic signature consisting of 131 genes. The signature correlates with Met activation and with response to anti-Met therapy (p<0.005) in in-vitro models. It also identifies breast cancer patients who are at high risk to develop an aggressive disease in six large published breast cancer patient cohorts (p<0.01, N>1000). Moreover, we have identified novel putative Met pathways, which correlate with Met activity and patient prognosis. This signature may facilitate personalized therapy by identifying patients who will respond to anti-Met therapy. Moreover, this novel approach may be applied for other tyrosine kinases and other malignancies.

Interferon-inducible guanylate binding protein (GBP2) is associated with better prognosis in breast cancer and indicates an efficient T cell response

BACKGROUND

Recently, interferon-inducible guanylate binding protein (GBP2) has been discussed as a possible control factor in tumor development, which is controlled by p53, and inhibits NF-Kappa B and Rac protein as well as expression of matrix metalloproteinase 9. However, the potential role that GBP2 plays in tumor development and prognosis has not yet been studied.

METHODS

We analyzed whether GBP2 mRNA levels are associated with metastasis-free interval in 766 patients with node negative breast carcinomas who did not receive systemic chemotherapy. Furthermore, response to anthracycline-based chemotherapy was studied in 768 breast cancer patients.

RESULTS

High expression of GBP2 in breast carcinomas was associated with better prognosis in the univariate (P < 0.001, hazard ratio 0.763, 95 % CI 0.650-0.896) as well as in the multivariate Cox analysis (P = 0.008, hazard ratio 0.731, 95 % CI 0.580-0.920) adjusted to the established clinical factors age, pT stage, grading, hormone and ERBB2 receptor status. The association was particularly strong in subgroups with high proliferation and positive estrogen receptor status but did not reach significance in carcinomas with low expression of proliferation associated genes. Besides its prognostic capacity, GBP2 also predicted pathologically complete response to anthracycline-based chemotherapy (P = 0.0037, odds ratio 1.39, 95 % CI 1.11-1.74). Interestingly, GBP2 correlated with a recently established T cell signature, indicating tumor infiltration with T cells (R = 0.607, P < 0.001).

CONCLUSION

GBP2 is associated with better prognosis in fast proliferating tumors and probably represents a marker of an efficient T cell response.

LAPTM4B allele *2 is associated with breast cancer susceptibility and prognosis

Background

Lysosome-associated protein transmembrane 4 beta (LAPTM4B) has two alleles named LAPTM4B*1 and LAPTM4B*2. Allele *1 contains only one copy of a 19-bp sequence at the 5′UTR in the first exon, whereas this sequence of allele*2 is duplicated and arrayed as a tandem repeat. Previous studies revealed that LAPTM4B polymorphisms contribute to the risk of certain types of cancers. This study aimed to investigate the polymorphism of LAPTM4B in breast cancer by analysis the correlation of LAPTM4B genotype with breast cancer susceptibility, clinicopathologic features and prognosis.

Methods

Genotyping of the LAPTM4B polymorphism was determined by PCR method. The expression levels of LAPTM4B in breast cancer tissues and breast cancer cell lines were determined by quantitative reverse-transcription PCR (qRT-PCR) analysis. The correlation of LAPTM4B genotype with clinicopathologic parameters and prognosis were assessed statistically.

Results

The results of qRT-PCR analysis indicated that LAPTM4B*2 was associated with the higher level of LAPTM4B expression compared with the LAPTM4B*1 in both breast cancer cell lines and breast cancer tissues. We found that LAPTM4B*2 was associated with an increased risk for breast cancer. LAPTM4B*2 was significantly associated with higher histopathologic grade, lymph node metastasis and poor prognosis.

Conclusion

LAPTM4B*2 is a risk factor associated with breast cancer susceptibility and poor prognosis. LAPTM4B*2 may be a potential predicative marker for the susceptibility, progression and metastasis of breast cancer.

LAPTM4B allele *2 is a marker of poor prognosis for gallbladder carcinoma

Background

Lysosomal protein transmembrane 4 beta (LAPTM4B) is a novel cancer-related gene which has two alleles designated LAPTM4B*1 and LAPTM4B*2. In this study we investigated the correlation of LAPTM4B genotype with prognosis and clinicopathologic features in patients who had undergone curative resection for gallbladder carcinoma (GBC).

Methodology/Principal Findings

PCR assay was performed to determine the LAPTM4B genotype in 85 patients. The correlation of LAPTM4B genotype with clinicopathologic parameters was assessed with the Chi-squared test. Differences in patient survival were determined by the Kaplan–Meier method. Multivariate analysis of prognostic factors was carried out with Cox regression analysis. Patients with LAPTM4B *2 had both significantly shorter overall survival (OS) and shorter disease-free survival (DFS) (both P<0.001). Multivariate analysis showed that LAPTM4B genotype is a prognostic factor for OS and DFS (both P<0.001).

Conclusions/Significance

LAPTM4B allele *2 is a risk factor associated with poor prognosis in patients with resected GBC, and LAPTM4B status may be therefore be useful preoperatively as an adjunct in evaluation of the operability of GBC.

Novel tumor subgroups of urothelial carcinoma of the bladder defined by integrated genomic analysis

PURPOSE

There is a need for improved subclassification of urothelial carcinoma (UC) at diagnosis. A major aim of this study was to search for novel genomic subgroups.

EXPERIMENTAL DESIGN

We assessed 160 tumors for genome-wide copy number alterations and mutation in genes implicated in UC. These comprised all tumor grades and stages and included 49 high-grade stage T1 (T1G3) tumors.

RESULTS

Our findings point to the existence of genomic subclasses of the "gold-standard" grade/stage groups. The T1G3 tumors separated into 3 major subgroups that differed with respect to the type and number of copy number events and to FGFR3 and TP53 mutation status. We also identified novel regions of copy number alteration, uncovered relationships between molecular events, and elucidated relationships between molecular events and clinico-pathologic features. FGFR3 mutant tumors were more chromosomally stable than their wild-type counterparts and a mutually exclusive relationship between FGFR3 mutation and overrepresentation of 8q was observed in non-muscle-invasive tumors. In muscle-invasive (MI) tumors, metastasis was positively associated with losses of regions on 10q (including PTEN), 16q and 22q, and gains on 10p, 11q, 12p, 19p, and 19q. Concomitant copy number alterations positively associated with TP53 mutation in MI tumors were losses on 16p, 2q, 4q, 11p, 10q, 13q, 14q, 16q, and 19p, and gains on 1p, 8q, 10q, and 12q. Significant complexity was revealed in events affecting chromosome 9.

CONCLUSIONS

These findings may lead to improved biologic understanding and the development of prognostic biomarkers. Novel regions of copy number alteration may reveal potential therapeutic targets.

Studying protein-protein interaction networks: a systems view on diseases

In order to better understand several cellular processes, it is helpful to study how various components make up the system. This systems perspective is supported by several modelling tools including network analysis. Networks of protein-protein interactions (PPI networks) offer a way to depict, visualize and quantify the functioning and relative importance of particular proteins in cell function. The toolkit of network analysis ranges from the local indices describing individual proteins (as network nodes) to global indicators of system architecture, describing the total interaction system (as the whole network). We briefly introduce some of these network indices and present a case study where the connectedness and potential functional relationships between certain disease proteins are inferred. We argue that network analysis can be used, in general, to improve databases, to infer novel functions, to quantify positional importance and to support predictions in pathogenesis studies. The systems perspective and network analysis can be of particular importance in studying diseases with complex molecular processes.

Feature extraction via composite scoring and voting in breast cancer

Identification and characterization of tumor subtypes using gene expression profiles of triple negative breast cancer patients. Microarray data of four breast cancer studies were pooled and evaluated. Molecular subtype classification was performed using random forest and a novel algorithm for feature extraction via composite scoring and voting. Biological and clinical properties were evaluated via GSEA, functional annotation clustering and clinical endpoint analysis. The subtype signatures are highly predictive for distant metastasis free survival of tamoxifen-treated patients. Consensus clustering and the novel algorithm proposed three triple negative subtypes. One subtype shows low E2F4 gene expression and is predictive for survival of ER negative breast cancer patients. The other two subtypes share commonalities with luminal B tumors. Classification of breast cancer expression profiles may reveal novel tumor subtypes, possessing clinical impact. Furthermore, subtype characterizing gene signatures might hold potential for novel strategies in cancer therapy.

LAPTM5 protein is a positive regulator of proinflammatory signaling pathways in macrophages

LAPTM5 (lysosomal-associated protein transmembrane 5) is a protein that is preferentially expressed in immune cells, and it interacts with the Nedd4 family of ubiquitin ligases. Recent studies in T and B cells identified LAPTM5 as a negative regulator of T and B cell receptor levels at the plasma membrane. Here we investigated the function of LAPTM5 in macrophages. We demonstrate that expression of LAPTM5 is required for the secretion of proinflammatory cytokines in response to Toll-like receptor ligands. We also show that RAW264.7 cells knocked down for LAPTM5 or macrophages from LAPTM5(-/-) mice exhibit reduced activation of NF-κB and MAPK signaling pathways mediated by the TNF receptor, as well as multiple pattern recognition receptors in various cellular compartments. TNF stimulation of LAPTM5-deficient macrophages leads to reduced ubiquitination of RIP1 (receptor-interacting protein 1), suggesting a role for LAPTM5 at the receptor-proximate level. Interestingly, we find that macrophages from LAPTM5(-/-) mice display up-regulated levels of A20, a ubiquitin-editing enzyme responsible for deubiquitination of RIP1 and subsequent termination of NF-κB activation. Our studies thus indicate that, in contrast to its negative role in T and B cell activation, LAPTM5 acts as a positive modulator of inflammatory signaling pathways and hence cytokine secretion in macrophages. They also highlight a role for the endosomal/lysosomal system in regulating signaling via cytokine and pattern recognition receptors.

Independent and functional validation of a multi-tumour-type proliferation signature

Background:

Previously we demonstrated that an mRNA signature reflecting cellular proliferation had strong prognostic value. As clinical applicability of signatures can be controversial, we sought to improve our marker’s clinical utility by validating its biological relevance, reproducibility in independent data sets and applicability using an independent technique.

Methods:

To facilitate signature evaluation with quantitative PCR (qPCR) a novel computational procedure was used to reduce the number of signature genes without significant information loss. These genes were validated in different human cancer cell lines upon serum starvation and in a 168 xenografts panel. Analyses were then extended to breast cancer and non-small-cell lung cancer (NSCLC) patient cohorts.

Results:

Expression of the qPCR-based signature was dramatically decreased under starvation conditions and inversely correlated with tumour volume doubling time in xenografts. The signature validated in breast cancer (hazard ratio (HR)=1.63, P<0.001, n=1820) and NSCLC adenocarcinoma (HR=1.64, P<0.001, n=639) microarray data sets. Lastly, qPCR in a node-negative, non-adjuvantly treated breast cancer cohort (n=129) showed that patients assigned to the high-proliferation group had worse disease-free survival (HR=2.25, P<0.05).

Conclusion:

We have developed and validated a qPCR-based proliferation signature. This test might be used in the clinic to select (early-stage) patients for specific treatments that target proliferation.

Gene interaction enrichment and network analysis to identify dysregulated pathways and their interactions in complex diseases

BACKGROUND

The molecular behavior of biological systems can be described in terms of three fundamental components: (i) the physical entities, (ii) the interactions among these entities, and (iii) the dynamics of these entities and interactions. The mechanisms that drive complex disease can be productively viewed in the context of the perturbations of these components. One challenge in this regard is to identify the pathways altered in specific diseases. To address this challenge, Gene Set Enrichment Analysis (GSEA) and others have been developed, which focus on alterations of individual properties of the entities (such as gene expression). However, the dynamics of the interactions with respect to disease have been less well studied (i.e., properties of components ii and iii).

RESULTS

Here, we present a novel method called Gene Interaction Enrichment and Network Analysis (GIENA) to identify dysregulated gene interactions, i.e., pairs of genes whose relationships differ between disease and control. Four functions are defined to model the biologically relevant gene interactions of cooperation (sum of mRNA expression), competition (difference between mRNA expression), redundancy (maximum of expression), or dependency (minimum of expression) among the expression levels. The proposed framework identifies dysregulated interactions and pathways enriched in dysregulated interactions; points out interactions that are perturbed across pathways; and moreover, based on the biological annotation of each type of dysregulated interaction gives clues about the regulatory logic governing the systems level perturbation. We demonstrated the potential of GIENA using published datasets related to cancer.

CONCLUSIONS

We showed that GIENA identifies dysregulated pathways that are missed by traditional enrichment methods based on the individual gene properties and that use of traditional methods combined with GIENA provides coverage of the largest number of relevant pathways. In addition, using the interactions detected by GIENA, specific gene networks both within and across pathways associated with the relevant phenotypes are constructed and analyzed.

Overexpression of LAPTM4B-35 is associated with poor prognosis in colorectal carcinoma

BACKGROUND

The purpose of this study was to determine whether lysosome-associated protein transmembrane-4 beta (LAPTM4B) overexpression is associated with the prognosis in patients with colorectal cancer.

METHODS

LAPTM4B expression was evaluated in colorectal cancer patients by Western blot analysis and immunohistochemistry. Univariate and multivariate analyses were performed to determine the association between LAPTM4B expression and prognosis.

RESULTS

Among the 136 patients with colorectal cancer, 51 patients had low LAPTM4B expression, and 85 patients had high LAPTM4B expression. The sensitivity and specificity of LAPTM4B overexpression were 62.5% and 100%, respectively. The 5-year overall survival (OS) rates for patients with high and low LAPTM4B expression were 37.38% and 98.04%, respectively (hazard ratio = 22.774; 95% confidence interval [CI], 5.287-98.091; P < .0001). The 5-year disease-free survival rate was 21.15% for patients in the high-expression group and 91.82% for patients in the low-expression group (hazard ratio = 11.674; 95% CI, 3.562-38.263; P < .0001).

CONCLUSIONS

LAPTM4B overexpression is an independent factor in colorectal cancer prognosis, and it may be an important potential biomarker.

Amplification and high-level expression of heat shock protein 90 marks aggressive phenotypes of human epidermal growth factor receptor 2 negative breast cancer

Introduction

Although human epidermal growth factor receptor 2 (HER2) positive or estrogen receptor (ER) positive breast cancers are treated with clinically validated anti-HER2 or anti-estrogen therapies, intrinsic and acquired resistance to these therapies appears in a substantial proportion of breast cancer patients and new therapies are needed. Identification of additional molecular factors, especially those characterized by aggressive behavior and poor prognosis, could prioritize interventional opportunities to improve the diagnosis and treatment of breast cancer.

Methods

We compiled a collection of 4,010 breast tumor gene expression data derived from 23 datasets that have been posted on the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. We performed a genome-scale survival analysis using Cox-regression survival analyses, and validated using Kaplan-Meier Estimates survival and Cox Proportional-Hazards Regression survival analyses. We conducted a genome-scale analysis of chromosome alteration using 481 breast cancer samples obtained from The Cancer Genome Atlas (TCGA), from which combined expression and copy number data were available. We assessed the correlation between somatic copy number alterations and gene expression using analysis of variance (ANOVA).

Results

Increased expression of each of the heat shock protein (HSP) 90 isoforms, as well as HSP transcriptional factor 1 (HSF1), was correlated with poor prognosis in different subtypes of breast cancer. High-level expression of HSP90AA1 and HSP90AB1, two cytoplasmic HSP90 isoforms, was driven by chromosome coding region amplifications and were independent factors that led to death from breast cancer among patients with triple-negative (TNBC) and HER2-/ER+ subtypes, respectively. Furthermore, amplification of HSF1 was correlated with higher HSP90AA1 and HSP90AB1 mRNA expression among the breast cancer cells without amplifications of these two genes. A collection of HSP90AA1, HSP90AB1 and HSF1 amplifications defined a subpopulation of breast cancer with up-regulated HSP90 gene expression, and up-regulated HSP90 expression independently elevated the risk of recurrence of TNBC and poor prognosis of HER2-/ER+ breast cancer.

Conclusions

Up-regulated HSP90 mRNA expression represents a confluence of genomic vulnerability that renders HER2 negative breast cancers more aggressive, resulting in poor prognosis. Targeting breast cancer with up-regulated HSP90 may potentially improve the effectiveness of clinical intervention in this disease.

LAPTM4B allele *2 is a marker of poor prognosis following hepatic tumor resection for hepatocellular carcinoma

Background

Lysosomal protein transmembrane 4 beta (LAPTM4B) is a gene related to hepatocellular carcinoma that has two alleles designated LAPTM4B*1 and LAPTM4B*2. This study aimed to investigate the correlation of LAPTM4B genotype with prognosis and clinicopathologic features in patients who have undergone resection for hepatocellular carcinoma (HCC).

Methodology/Principal Findings

The LAPTM4B genotype was analyzed by PCR in 68 patients who had undergone curative hepatic resection for hepatocellular carcinoma. The correlation of LAPTM4B genotype with clinicopathologic parameters was assessed with the Chi-squared test. Differences in patient survival were determined by the Kaplan–Meier method. Multivariate analysis of prognostic factors was carried out with Cox regression analysis. Patients with LAPTM4B *2 had both significantly shorter overall survival (OS) and shorter disease-free survival (DFS) (both P<0.001). Multivariate analysis showed that LAPTM4B genotype is an independent prognostic factor for OS and DFS (both P<0.001).

Conclusions/Significance

Allele *2 of LAPTM4B is a risk factor associated with poor prognosis in patients with resected HCC. LAPTM4B status may be useful preoperatively as an adjunct in evaluation of the operability of HCC.

Telomeric allelic imbalance indicates defective DNA repair and sensitivity to DNA-damaging agents

DNA repair competency is one determinant of sensitivity to certain chemotherapy drugs, such as cisplatin. Cancer cells with intact DNA repair can avoid the accumulation of genome damage during growth and also can repair platinum-induced DNA damage. We sought genomic signatures indicative of defective DNA repair in cell lines and tumors and correlated these signatures to platinum sensitivity. The number of subchromosomal regions with allelic imbalance extending to the telomere (N(tAI)) predicted cisplatin sensitivity in vitro and pathologic response to preoperative cisplatin treatment in patients with triple-negative breast cancer (TNBC). In serous ovarian cancer treated with platinum-based chemotherapy, higher levels of N(tAI) forecast a better initial response. We found an inverse relationship between BRCA1 expression and N(tAI) in sporadic TNBC and serous ovarian cancers without BRCA1 or BRCA2 mutation. Thus, accumulation of telomeric allelic imbalance is a marker of platinum sensitivity and suggests impaired DNA repair.

SIGNIFICANCE

Mutations in BRCA genes cause defects in DNA repair that predict sensitivity to DNA damaging agents, including platinum; however, some patients without BRCA mutations also benefit from these agents. NtAI, a genomic measure of unfaithfully repaired DNA, may identify cancer patients likely to benefit from treatments targeting defective DNA repair.

A phenotypic mouse model of basaloid breast tumors

Chemotherapeutic strategies that target basal-like breast tumors are difficult to design without understanding their cellular and molecular basis. Here, we induce tumors in mice by carcinogen administration, creating a phenocopy of tumors with the diagnostic and functional aspects of human triple negative disease (including EGFR expression/lack of erbB, estrogen-independent growth and co-clustering of the transcriptome with other basaloid models). These tumor strains are a complement to established mouse models that are based on mutations in Brca1 and/or p53. Tumors comprise two distinct cell subpopulations, basal and luminal epithelial cells. These cell fractions were purified by flow cytometry, and only basal cell fractions found to have tumor initiating activity (cancer stem cells). The phenotype of serially regenerated tumors was stable, and irrespective of tumor precursor cell. Tumors were passaged entirely in vivo and serial generations tested for their phenotypic stability. The relative chemo-sensitivity of basal and luminal cells were evaluated. Upon treatment with anthracycline, tumors were effectively de-bulked, but recurred; this correlated with maintenance of a high rate of basal cell division throughout the treatment period. Thus, these tumors grow as robust cell mixtures of basal bipotential tumor initiating cells alongside a luminal majority, and the cellular response to drug administration is dominated by the distinct biology of the two cell types. Given the ability to separate basal and luminal cells, and the discovery potential of this approach, we propose that this mouse model could be a convenient one for preclinical studies.

Parallel evolution under chemotherapy pressure in 29 breast cancer cell lines results in dissimilar mechanisms of resistance

Background

Developing chemotherapy resistant cell lines can help to identify markers of resistance. Instead of using a panel of highly heterogeneous cell lines, we assumed that truly robust and convergent pattern of resistance can be identified in multiple parallel engineered derivatives of only a few parental cell lines.

Methods

Parallel cell populations were initiated for two breast cancer cell lines (MDA-MB-231 and MCF-7) and these were treated independently for 18 months with doxorubicin or paclitaxel. IC50 values against 4 chemotherapy agents were determined to measure cross-resistance. Chromosomal instability and karyotypic changes were determined by cytogenetics. TaqMan RT-PCR measurements were performed for resistance-candidate genes. Pgp activity was measured by FACS.

Results

All together 16 doxorubicin- and 13 paclitaxel-treated cell lines were developed showing 2–46 fold and 3–28 fold increase in resistance, respectively. The RT-PCR and FACS analyses confirmed changes in tubulin isofom composition, TOP2A and MVP expression and activity of transport pumps (ABCB1, ABCG2). Cytogenetics showed less chromosomes but more structural aberrations in the resistant cells.

Conclusion

We surpassed previous studies by parallel developing a massive number of cell lines to investigate chemoresistance. While the heterogeneity caused evolution of multiple resistant clones with different resistance characteristics, the activation of only a few mechanisms were sufficient in one cell line to achieve resistance.

CERT depletion predicts chemotherapy benefit and mediates cytotoxic and polyploid-specific cancer cell death through autophagy induction

Chromosomal instability (CIN) has been implicated in multidrug resistance and the silencing of the ceramide transporter, CERT, promotes sensitization to diverse cytotoxics. An improved understanding of mechanisms governing multidrug sensitization might provide insight into pathways contributing to the death of CIN cancer cells. Using an integrative functional genomics approach, we find that CERT-specific multidrug sensitization is associated with enhanced autophagosome-lysosome flux, resulting from the expression of LAMP2 following CERT silencing in colorectal and HER2(+) breast cancer cell lines. Live cell microscopy analysis revealed that CERT depletion induces LAMP2-dependent death of polyploid cells following exit from mitosis in the presence of paclitaxel. We find that CERT is relatively over-expressed in HER2(+) breast cancer and CERT protein expression acts as an independent prognostic variable and predictor of outcome in adjuvant chemotherapy-treated patients with primary breast cancer. These data suggest that the induction of LAMP2-dependent autophagic flux through CERT targeting may provide a rational approach to enhance multidrug sensitization and potentiate the death of polyploid cells following paclitaxel exposure to limit the acquisition of CIN and intra-tumour heterogeneity.

Association of LAPTM4B gene polymorphism with breast cancer susceptibility

BACKGROUND

Lysosome associated protein transmembrane 4 beta (LAPTM4B) was a cancer-associated gene that is mapped to chromosome 8q22 with seven exons and six introns. LAPTM4B gene polymorphism has been reported to be significantly associated with susceptibility of several solid tumors.

METHODS

We performed a case-control study was to investigate the association between LAPTM4B polymorphism and the risk of breast cancer in 732 breast cancer patients and 649 controls.

RESULTS

A significant difference in the frequency of LAPTM4B*2 was observed between the patients and the controls (P < 0.01). Using the LAPTM4B*1/1 genotype as a reference, we found that LAPTM4B allelic variation was significantly associated with breast cancer occurrence, with adjusted odds ratios of 1.387 (95%CI = 1.111-1.730) for LAPTM4B*1/2 and 1.592 (95% CI = 1.043-2.430) for LAPTM4B*2/2 genotype.

CONCLUSION

Our results suggested that LAPTM4B*2 is associated with an increased risk of breast cancer in the Chinese women population and may be a risk factor of breast cancer.

MicroRNAs associated with mitogen-activated protein kinase in human pancreatic cancer

Aberrant expression of microRNAs (miRNA) is associated with phenotypes of various cancers, including pancreatic cancer. However, the mechanism of the aberrant expression is largely unknown. Activation of the mitogen-activated protein kinase (MAPK) signaling pathway plays a crucial role in gene expression related to the malignant phenotype of pancreatic cancer. Hence, we studied the role of MAPK in the aberrant expression of miRNAs in pancreatic cancer cells. The alterations in expression of 183 miRNAs induced by activation or inactivation of MAPK were assayed in cultured pancreatic cancer cells and HEK293 cells by means of the quantitative real-time PCR method. We found that four miRNAs, namely, miR-7-3, miR-34a, miR-181d, and miR-193b, were preferentially associated with MAPK activity. Among these miRNAs, miR-7-3 was upregulated by active MAPK, whereas the others were downregulated. Promoter assays indicated that the promoter activities of the host genes of miR-7-3 and miR-34a were both downregulated by alteration in MAPK activity. Exogenous overexpression of the MAPK-associated miRNAs had the effect of inhibition of the proliferation of cultured pancreatic cancer cells; miR-193b was found to exhibit the most remarkable inhibition. A search for target genes of miR-193b led to identification of CCND1, NT5E, PLAU, STARD7, STMN1, and YWHAZ as the targets. Translational suppression of these genes by miR-193b was confirmed by reporter assay. These results indicate that activation of MAPK may play a significant role in aberrant expression of miRNAs and their associated phenotypes in pancreatic cancer.

Tumour heterogeneity and drug resistance: personalising cancer medicine through functional genomics

Intrinsic and acquired drug resistance leads to the eventual failure of cancer treatment regimens in the majority of advanced solid tumours. Understanding drug resistance mechanisms will prove vital in the future development of personalised therapeutic approaches. Functional genomics technologies may permit the discovery of predictive biomarkers by unravelling pathways involved in drug resistance and allow the systematic identification of novel therapeutic targets. Such technologies offer the opportunity to develop personalised treatments and diagnostic tools that may improve the survival and quality of life of patients with cancer. However, despite progress in biomarker and drug target discovery, inter-tumour and intra-tumour molecular heterogeneity will limit the effective treatment of this disease. Combining an improved understanding of cancer cell survival mechanisms associated with intra-tumour heterogeneity and drug resistance may allow the selection of patients for specific treatment regimens that will maximise benefit, limit the acquisition of drug resistance and lessen the impact of deleterious side effects.

Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer

Introduction

Infiltration of breast tumors by tumor-infiltrating lymphocytes (TIL) has been associated with sensitivity to anthracycline-based chemotherapy. However, it is unclear whether this is true within the estrogen receptor-alpha (ER)-negative subset of breast tumors that frequently manifest high TIL levels.

Methods

The association of TIL with short-term and long-term clinical response to anthracycline-based therapy was assessed in two independent ER-negative breast cancer cohorts in which patients were categorized as TIL-high or TIL-low. We defined an eight-gene lymphocyte mRNA expression signature (including CD19, CD3D, CD48, GZMB, LCK, MS4A1, PRF1, and SELL) and used unsupervised hierarchical clustering to examine the association between TIL and short-term response to neoadjuvant chemotherapy in a previously published cohort of ER-negative tumors (n = 113). We also examined the association between TIL and long-term chemotherapeutic efficacy in a second cohort of ER-negative tumors (n = 255) with longer than 6 years of median follow-up by using tissue microarrays and immunohistochemistry (IHC) for detection of CD3, CD8, CD4, CD20, and TIA-1.

Results

In patients with ER-negative tumors treated with neoadjuvant anthracycline-based chemotherapy, pathologic complete responses (pCRs) were achieved by 23 (74%) of 31 TIL-high patients and 25 (31%) of 80 TIL-low patients (odds ratio (OR), 6.33; 95% confidence interval (CI), 2.49 to 16.08; P < 0.0001). Multivariate logistic regression with standard clinicopathologic features demonstrated that only tumor size (P = 0.037) and TIL status (P = 0.001) were independent predictors of anthracycline response. In the second cohort, adjuvant anthracycline-based therapy was associated with increased disease-free survival (DFS) only in patients with high levels of intraepithelial CD3⁺ TIL (P = 0.0023). In contrast, outcomes after CMF treatment (cyclophosphamide, methotrexate, and fluorouracil) showed no association with CD3 status. In both cohorts, cytotoxic T-cells were the primary TIL subtype associated with anthracycline sensitivity. Finally, TIL significantly predicted anthracycline sensitivity for both the Her2-positive and triple-negative tumor phenotypes.

Conclusions

ER-negative breast cancers with high levels of TIL have heightened sensitivity to anthracycline-based chemotherapy, as assessed by the immediate response to neoadjuvant therapy and long-term outcome following adjuvant therapy. Investigations of TIL-based predictive tests to identify patients likely to benefit from anthracycline-based treatments are warranted.

Improving gene expression data interpretation by finding latent factors that co-regulate gene modules with clinical factors

Background

In the analysis of high-throughput data with a clinical outcome, researchers mostly focus on genes/proteins that show first-order relations with the clinical outcome. While this approach yields biomarkers and biological mechanisms that are easily interpretable, it may miss information that is important to the understanding of disease mechanism and/or treatment response. Here we test the hypothesis that unobserved factors can be mobilized by the living system to coordinate the response to the clinical factors.

Results

We developed a computational method named Guided Latent Factor Discovery (GLFD) to identify hidden factors that act in combination with the observed clinical factors to control gene modules. In simulation studies, the method recovered masked factors effectively. Using real microarray data, we demonstrate that the method identifies latent factors that are biologically relevant, and extracts more information than analyzing only the first-order response to the clinical outcome.

Conclusions

Finding latent factors using GLFD brings extra insight into the mechanisms of the disease/drug response. The R code of the method is available at http://userwww.service.emory.edu/~tyu8/GLFD.

A role for the ubiquitin ligase Nedd4 in membrane sorting of LAPTM4 proteins

BACKGROUND

The lysosome associated protein transmembrane (LAPTM) family is comprised of three members: LAPTM5, LAPTM4a and LAPTM4b, with the latter previously shown to be overexpressed in numerous cancers. While we had demonstrated earlier the requirement of the E3 ubiquitin ligase Nedd4 for LAPTM5 sorting to lysosomes, the regulation of sorting of LAPTM4 proteins is less clear.

METHODOLOGY/PRINCIPAL FINDINGS

Here we show that LAPTM4a and LAPTM4b are localized to the lysosome, but unique to LAPTM4b, a fraction of it is present at the plasma membrane and its overexpression induces the formation of actin-based membrane protrusions. We demonstrate that LAPTM4s, like LAPTM5, are able to co-immunoprecipitate with the E3 ubiquitin ligase Nedd4, an interaction that is dependent on LAPTM4 PY motifs and plays a role in membrane sorting. Accordingly, in Nedd4 knockout mouse embryonic fibroblasts (MEFs), LAPTM4a and LAPTM4b show reduced lysosomal localization. Moreover, lack of PY motifs leads to enhanced missorting of LAPTM4b to the plasma membrane instead of the lysosome.

CONCLUSIONS/SIGNIFICANCE

These results suggest that while some requisites of LAPTM5 lysosomal sorting are conserved among LAPTM4 proteins, LAPTM4a and LAPTM4b have also developed distinct sorting requirements.

Do anthracyclines still have a role in adjuvant chemotherapy of breast cancer?

Anthracycline-based regimens became the standard of care for early breast cancer patients based on the survival advantage they provide over nonanthracycline-containing regimens. The addition of taxanes, and subsequently trastuzumab in HER2-overexpressing patients, to anthracyclines further improved their efficacy in several studies involving high-risk early breast cancer patients. Concern over toxicity initially surfaced after anthracyclines were reported to carry an increased risk of cardiotoxicity and secondary leukemia. Trastuzumab has since been shown to compound the risk of cardiotoxicity in patients who have received an anthracycline. This has led to the development of regimens featuring a taxane without an anthracycline; these protocols vary in design and have different toxicity and efficacy profiles. Ongoing investigations are centered on the optimization of nonanthracycline regimens, prospective exploration of molecular markers to identify populations of patients who will derive maximal benefit from anthracycline-based chemotherapy, and the identification of less cardiotoxic formulations of existing anthracycline agents. Perhaps most importantly, a rapidly growing understanding of the biological heterogeneity of breast cancer is likely to lead to an individualized standard of care guided by particular patient and tumor characteristics.

Inferring pleiotropy by network analysis: linked diseases in the human PPI network

Background

Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the ones connecting heart disease and obesity.

Results

We quantified their overlap, and based on the identified topological patterns, we inferred the structural disease-relatedness of several proteins. Literature data provide a functional look of them, well supporting our findings. For example, the inferred structurally important role of the PDZ domain-containing protein GIPC1 in diabetes is supported despite the lack of this information in the Online Mendelian Inheritance in Man database. Several key mediator proteins identified here clearly has pleiotropic effects, supported by ample evidence for their general but always of only secondary importance.

Conclusions

We suggest that studying central nodes in mediator networks may contribute to better understanding and quantifying pleiotropy. Network analysis provides potentially useful tools here, as well as helps in improving databases.

Lysosomal transmembrane protein LAPTM4B promotes autophagy and tolerance to metabolic stress in cancer cells

Amplification of chromosome 8q22, which includes the gene for lysosomal associated transmembrane protein LAPTM4B, has been linked to de novo anthracycline resistance in primary breast cancers with poor prognosis. LAPTM4B overexpression can induce cytosolic retention of anthracyclines and decrease drug-induced DNA damage. In this study, we tested the hypothesis that LAPTM4B may contribute to tumor cell growth or survival in the absence of a chemotherapeutic exposure. In mammary cells, LAPTM4B protein was localized in lysosomes where its depletion increased membrane permeability, pH, cathepsin release, and cellular apoptosis. Loss of LAPTM4B also inhibited later stages of autophagy by blocking maturation of the autophagosome, thereby rendering cells more sensitive to nutrient deprivation or hypoxia. Conversely, enforced overexpression of LAPTM4B promoted autophagic flux and cell survival during in vitro starvation and stimulated more rapid tumor growth in vivo. Together, our results indicate that LAPTM4B is required for lysosome homeostasis, acidification, and function, and that LAPTM4B renders tumor cells resistant to lysosome-mediated cell death triggered by environmental and genotoxic stresses.

14-3-3 proteins as potential therapeutic targets

The 14-3-3 family of phosphoserine/phosphothreonine-binding proteins dynamically regulates the activity of client proteins in various signaling pathways that control diverse physiological and pathological processes. In response to environmental cues, 14-3-3 proteins orchestrate the highly regulated flow of signals through complex networks of molecular interactions to achieve well-controlled physiological outputs, such as cell proliferation or differentiation. Accumulating evidence now supports the concept that either an abnormal state of 14-3-3 protein expression, or dysregulation of 14-3-3/client protein interactions, contributes to the development of a large number of human diseases. In particular, clinical investigations in the field of oncology have demonstrated a correlation between upregulated 14-3-3 levels and poor survival of cancer patients. These studies highlight the rapid emergence of 14-3-3 proteins as a novel class of molecular target for potential therapeutic intervention. The current status of 14-3-3 modulator discovery is discussed.

Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response

BACKGROUND

Genome scale expression profiling of human tumor samples is likely to yield improved cancer treatment decisions. However, identification of clinically predictive or prognostic classifiers can be challenging when a large number of genes are measured in a small number of tumors.

RESULTS

We describe an unsupervised method to extract robust, consistent metagenes from multiple analogous data sets. We applied this method to expression profiles from five "double negative breast cancer" (DNBC) (not expressing ESR1 or HER2) cohorts and derived four metagenes. We assessed these metagenes in four similar but independent cohorts and found strong associations between three of the metagenes and agent-specific response to neoadjuvant therapy. Furthermore, we applied the method to ovarian and early stage lung cancer, two tumor types that lack reliable predictors of outcome, and found that the metagenes yield predictors of survival for both.

CONCLUSIONS

These results suggest that the use of multiple data sets to derive potential biomarkers can filter out data set-specific noise and can increase the efficiency in identifying clinically accurate biomarkers.

Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies

Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted "driver" signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.

Reversal of endocrine resistance in breast cancer: interrelationships among 14-3-3ζ, FOXM1, and a gene signature associated with mitosis

INTRODUCTION

Despite the benefits of estrogen receptor (ER)-targeted endocrine therapies in breast cancer, many tumors develop resistance. 14-3-3 ζ/YWHAZ, a member of the 14-3-3 family of conserved proteins, is over-expressed in several types of cancer, and our previous work showed that high expression of 14-3-3ζ in ER-positive breast cancers was associated with a poor clinical outcome for women on tamoxifen. Therefore, we now probe the role of 14-3-3ζ in endocrine resistance, and we examine the functional dimensions and molecular basis that underlie 14-3-3ζ activities.

METHODS

From analyses of four independent breast cancer microarray datasets from nearly 400 women, we characterized a gene signature that correlated strongly with high expression of 14-3-3ζ in breast tumors and examined its association with breast cancer molecular subtypes and clinical-pathological features. We investigated the effects of altering 14-3-3ζ levels in ER-positive, endocrine sensitive and resistant breast cancer cells on the regulation of 14-3-3ζ signature genes, and on cellular signaling pathways and cell phenotypic properties.

RESULTS

The gene signature associated with high 14-3-3ζ levels in breast tumors encompassed many with functions in mitosis and cytokinesis, including aurora kinase-B, polo-like kinase-1, CDC25B, and BIRC5/survivin. The gene signature correlated with early recurrence and risk of metastasis, and was found predominantly in luminal B breast cancers, the more aggressive ER-positive molecular subtype. The expression of the signature genes was significantly decreased or increased upon reduction or overexpression of 14-3-3ζ in ER-positive breast cancer cells, indicating their coregulation. 14-3-3ζ also played a critical role in the regulation of FOXM1, with 14-3-3ζ acting upstream of FOXM1 to regulate cell division-signature genes. Depletion of 14-3-3ζ markedly increased apoptosis, reduced proliferation and receptor tyrosine kinase (HER2 and EGFR) signaling, and, importantly, reversed endocrine resistance.

CONCLUSIONS

This study reveals that 14-3-3ζ is a key predictive marker for risk of failure on endocrine therapy and serves a pivotal role impacting growth factor signaling, and promoting cell survival and resistance to endocrine therapies. Targeting 14-3-3ζ and its coregulated proteins, such as FOXM1, should prove valuable in restoring endocrine sensitivity and reducing risk of breast cancer recurrence.

Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management.