Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival

Transcription factor E2F3 activates CDC25B to regulate DNA damage and promote mitoxantrone resistance in stomach adenocarcinoma

BACKGROUND

CDC25B, as a member of the cell cycle regulating protein family, is located in the cytoplasm and is involved in the transition of the cell cycle and mitosis. CDC25B is highly expressed in various tumors and is a newly discovered oncogene. This study aimed to investigate the impact of CDC25B on mitoxantrone resistance in stomach adenocarcinoma (STAD) and its possible mechanisms.

METHODS

This study analyzed the expression of CDC25B and its potential transcription factor E2F3 in STAD, as well as the IC50 values of tumor tissues by bioinformatics analysis. Expression levels of CDC25B and E2F3 in STAD cells were measured by qRT-PCR. MTT was utilized to evaluate cell viability and IC50 values of STAD cells, and comet assay was utilized to analyze the level of DNA damage in STAD cells. Western blot was used to analyze the expression of DNA damage-related proteins. The targeting relationship between E2F3 and CDC25B was validated by dual-luciferase and ChIP assays.

RESULTS

Bioinformatics analysis and molecular experiments showed that CDC25B and E2F3 were highly expressed in STAD, and CDC25B was enriched in the mismatch repair and nucleotide excision repair pathways. The IC50 values of tumor tissues with high expression of CDC25B were relatively high. Dual-luciferase and ChIP assays confirmed that CDC25B could be transcriptionally activated by E2F3. Cell experiments revealed that CDC25B promoted mitoxantrone resistance in STAD cells by regulating DNA damage. Further research found that low expression of E2F3 inhibited mitoxantrone resistance in STAD cells by DNA damage, but overexpression of CDC25B reversed the impact of E2F3 knockdown on mitoxantrone resistance in STAD cells.

CONCLUSION

This study confirmed a novel mechanism by which E2F3/CDC25B mediated DNA damage to promote mitoxantrone resistance in STAD cells, providing a new therapeutic target for STAD treatment.

Mitochondrial adaptation decreases drug sensitivity of persistent triple negative breast cancer cells surviving combinatory and sequential chemotherapy

Triple negative breast cancer (TNBC) is an aggressive malignancy for which chemotherapy remains the standard treatment. However, between 3 and 5 years after chemotherapy, about half patients will relapse and it is essential to identify vulnerabilities of cancer cells surviving neoadujuvant therapy. In this study, we established persistent TNBC cell models after treating MDA-MB-231 and SUM159-PT TNBC cell lines with epirubicin and cyclophosphamide, and then with paclitaxel, for a total of 18 weeks. The resulting chemo-persistent cell lines were more proliferative, both in vitro and in xenografted mice. Interestingly, MDA-MB-231 persistent cells became less sensitive to chemotherapeutic drugs, whereas SUM159-PT persistent cells kept similar sensitivity compared to control cells. The reduced sensitivity to chemotherapy in MDA-MB-231 persistent cells was found to be associated with an increased oxidative phosphorylation (OXPHOS) and modified levels of tricarboxylic acid cycle (TCA) intermediates. Integration of data from proteomics and metabolomics demonstrated TCA cycle among the most upregulated pathways in MDA-MB-231 persistent cells. The absence of glucose and pyruvate impeded OXPHOS in persistent cells, while the absence of glutamine did not. In contrast, OXPHOS was not modified in control cells independently of TCA substrates, indicating that MDA-MB-231 persistent cells evolved towards a more pyruvate dependent profile. Finally, the inhibition of pyruvate entry into mitochondria with UK-5099 reduced OXPHOS and re-sensitized persistent cells to therapeutic agents. Together, these findings suggest that targeting mitochondrial pyruvate metabolism may help to overcome mitochondrial adaptation of chemo-persistent TNBC.

Systematic review of comparative transcriptomic studies of cellular resistance to genotoxic stress

The development of resistance by tumor cells to various types of therapy is a significant problem that decreases the effectiveness of oncology treatments. For more than two decades, comparative transcriptomic studies of tumor cells with different sensitivities to ionizing radiation and chemotherapeutic agents have been conducted in order to identify the causes and mechanisms underlying this phenomenon. However, the results of such studies have little in common and often contradict each other. We have assumed that a systematic analysis of a large number of such studies will provide new knowledge about the mechanisms of development of therapeutic resistance in tumor cells. Our comparison of 123 differentially expressed gene (DEG) lists published in 98 papers suggests a very low degree of consistency between the study results. Grouping the data by type of genotoxic agent and tumor type did not increase the similarity. The most frequently overexpressed genes were found to be those encoding the transport protein ABCB1 and the antiviral defense protein IFITM1. We put forward a hypothesis that the role played by the overexpression of the latter in the development of resistance may be associated not only with the stimulation of proliferation, but also with the limitation of exosomal communication and, as a result, with a decrease in the bystander effect. Among down regulated DEGs, BNIP3 was observed most frequently. The expression of BNIP3, together with BNIP3L, is often suppressed in cells resistant to non-platinum genotoxic chemotherapeutic agents, whereas it is increased in cells resistant to ionizing radiation. These observations are likely to be mediated by the binary effects of these gene products on survival, and regulation of apoptosis and autophagy. The combined data also show that even such obvious mechanisms as inhibition of apoptosis and increase of proliferation are not universal but show multidirectional changes.

Interpretable Machine Learning Models to Predict the Resistance of Breast Cancer Patients to Doxorubicin from Their microRNA Profiles

Doxorubicin is a common treatment for breast cancer. However, not all patients respond to this drug, which sometimes causes life-threatening side effects. Accurately anticipating doxorubicin-resistant patients would therefore permit to spare them this risk while considering alternative treatments without delay. Stratifying patients based on molecular markers in their pretreatment tumors is a promising approach to advance toward this ambitious goal, but single-gene gene markers such as HER2 expression have not shown to be sufficiently predictive. The recent availability of matched doxorubicin-response and diverse molecular profiles across breast cancer patients permits now analysis at a much larger scale. 16 machine learning algorithms and 8 molecular profiles are systematically evaluated on the same cohort of patients. Only 2 of the 128 resulting models are substantially predictive, showing that they can be easily missed by a standard-scale analysis. The best model is classification and regression tree (CART) nonlinearly combining 4 selected miRNA isoforms to predict doxorubicin response (median Matthew correlation coefficient (MCC) and area under the curve (AUC) of 0.56 and 0.80, respectively). By contrast, HER2 expression is significantly less predictive (median MCC and AUC of 0.14 and 0.57, respectively). As the predictive accuracy of this CART model increases with larger training sets, its update with future data should result in even better accuracy.

ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo

To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.

TGF-β induced reprogramming and drug resistance in triple-negative breast cells

BACKGROUND

The development of drug resistance remains to be a major cause of therapeutic failure in breast cancer patients. How drug-sensitive cells first evade drug inhibition to proliferate remains to be fully investigated.

METHODS

Here we characterized the early transcriptional evolution in response to TGF-β in the human triple-negative breast cells through bioinformatical analysis using a published RNA-seq dataset, for which MCF10A cells were treated with 5 ng/ml TGF-β1 for 0 h, 24 h, 48 h and 72 h, and the RNA-seq were performed in biological duplicates. The protein-protein interaction networks of the differentially expressed genes were constructed. KEGG enrichment analysis, cis-regulatory sequence analysis and Kaplan-Meier analysis were also performed to analyze the cellular reprograming induced by TGF-β and its contribution to the survival probability decline of breast cancer patients.

RESULT

Transcriptomic analysis revealed that cell growth was severely suppressed by TGF-β in the first 24 h but this anti-proliferate impact attenuated between 48 h and 72 h. The oncogenic actions of TGF-β happened within the same time frame with its anti-proliferative effects. In addition, sustained high expression of several drug resistance markers was observed after TGF-β treatment. We also identified 17 TGF-β induced genes that were highly correlated with the survival probability decline of breast cancer patients.

CONCLUSION

Together, TGF-β plays an important role in tumorigenesis and the development of drug resistance, which implies potential therapeutic strategies targeting the early-stage TGF-β signaling activities.

Role of the NUDT Enzymes in Breast Cancer

Despite global research efforts, breast cancer remains the leading cause of cancer death in women worldwide. The majority of these deaths are due to metastasis occurring years after the initial treatment of the primary tumor and occurs at a higher frequency in hormone receptor-positive (Estrogen and Progesterone; HR+) breast cancers. We have previously described the role of NUDT5 (Nudix-linked to moiety X-5) in HR+ breast cancer progression, specifically with regards to the growth of breast cancer stem cells (BCSCs). BCSCs are known to be the initiators of epithelial-to-mesenchyme transition (EMT), metastatic colonization, and growth. Therefore, a greater understanding of the proteins and signaling pathways involved in the metastatic process may open the door for therapeutic opportunities. In this review, we discuss the role of NUDT5 and other members of the NUDT family of enzymes in breast and other cancer types. We highlight the use of global omics data based on our recent phosphoproteomic analysis of progestin signaling pathways in breast cancer cells and how this experimental approach provides insight into novel crosstalk mechanisms for stratification and drug discovery projects aiming to treat patients with aggressive cancer.

The Breast Cancer Stem Cells Traits and Drug Resistance

Drug resistance is a major challenge in breast cancer (BC) treatment at present. Accumulating studies indicate that breast cancer stem cells (BCSCs) are responsible for the BC drugs resistance, causing relapse and metastasis in BC patients. Thus, BCSCs elimination could reverse drug resistance and improve drug efficacy to benefit BC patients. Consequently, mastering the knowledge on the proliferation, resistance mechanisms, and separation of BCSCs in BC therapy is extremely helpful for BCSCs-targeted therapeutic strategies. Herein, we summarize the principal BCSCs surface markers and signaling pathways, and list the BCSCs-related drug resistance mechanisms in chemotherapy (CT), endocrine therapy (ET), and targeted therapy (TT), and display therapeutic strategies for targeting BCSCs to reverse drug resistance in BC. Even more importantly, more attention should be paid to studies on BCSC-targeted strategies to overcome the drug resistant dilemma of clinical therapies in the future.

Radiomics of hepatocellular carcinoma

The diagnosis of hepatocellular carcinoma relies largely on non-invasive imaging, and is well suited for radiomics analysis. Radiomics is an emerging method for quantification of tumor heterogeneity by mathematically analyzing the spatial distribution and relationships of gray levels in medical images. The published studies on radiomics analysis of HCC provide encouraging data demonstrating potential utility for prediction of tumor biology, molecular profiles, post-therapy response, and outcome. The combination of radiomics data and clinical/laboratory information provides added value in many studies. Radiomics is a multi-step process that requires optimization and standardization, the development of semi-automated or automated segmentation methods, robust data quality control, and refinement of algorithms and modeling approaches for high-throughput data analysis. While radiomics remains largely in the research setting, the strong associations of predictive models and nomograms with certain pathologic, molecular, and immune markers with tumor aggressiveness and patient outcomes, provide great potential for clinical applications to inform optimized treatment strategies and patient prognosis.

Mechanisms of Action of EGFR Tyrosine Kinase Receptor Incorporated in Extracellular Vesicles

EGFR and some of the cognate ligands extensively traffic in extracellular vesicles (EVs) from different biogenesis pathways. EGFR belongs to a family of four homologous tyrosine kinase receptors (TKRs). This family are one of the major drivers of cancer and is involved in several of the most frequent malignancies such as non-small cell lung cancer, breast cancer, colorectal cancer and ovarian cancer. The carrier EVs exert crucial biological effects on recipient cells, impacting immunity, pre-metastatic niche preparation, angiogenesis, cancer cell stemness and horizontal oncogene transfer. While EV-mediated EGFR signalling is important to EGFR-driven cancers, little is known about the precise mechanisms by which TKRs incorporated in EVs play their biological role, their stoichiometry and associations to other proteins relevant to cancer pathology and EV biogenesis, and their means of incorporation in the target cell. In addition, it remains unclear whether different subtypes of EVs incorporate different complexes of TKRs with specific functions. A raft of high spatial and temporal resolution methods is emerging that could solve these and other questions regarding the activity of EGFR and its ligands in EVs. More importantly, methods are emerging to block or mitigate EV activity to suppress cancer progression and drug resistance. By highlighting key findings and areas that remain obscure at the intersection of EGFR signalling and EV action, we hope to cross-fertilise the two fields and speed up the application of novel techniques and paradigms to both.

Apigenin by targeting hnRNPA2 sensitizes triple-negative breast cancer spheroids to doxorubicin-induced apoptosis and regulates expression of ABCC4 and ABCG2 drug efflux transporters

Acquired resistance to doxorubicin is a major hurdle in triple-negative breast cancer (TNBC) therapy, emphasizing the need to identify improved strategies. Apigenin and other structurally related dietary flavones are emerging as potential chemo-sensitizers, but their effect on three-dimensional TNBC spheroid models has not been investigated. We previously showed that apigenin associates with heterogeneous ribonuclear protein A2/B1 (hnRNPA2), an RNA-binding protein involved in mRNA and co-transcriptional regulation. However, the role of hnRNPA2 in apigenin chemo-sensitizing activity has not been investigated. Here, we show that apigenin induced apoptosis in TNBC spheroids more effectively than apigenin-glycoside, owing to higher cellular uptake. Moreover, apigenin inhibited the growth of TNBC patient-derived organoids at an in vivo achievable concentration. Apigenin sensitized spheroids to doxorubicin-induced DNA damage, triggering caspase-9-mediated intrinsic apoptotic pathway and caspase-3 activity. Silencing of hnRNPA2 decreased apigenin-induced sensitization to doxorubicin in spheroids by diminishing apoptosis and partly abrogated apigenin-mediated reduction of ABCC4 and ABCG2 efflux transporters. Together these findings provide novel insights into the critical role of hnRNPA2 in mediating apigenin-induced sensitization of TNBC spheroids to doxorubicin by increasing the expression of efflux transporters and apoptosis, underscoring the relevance of using dietary compounds as a chemotherapeutic adjuvant.

Can image analysis provide evidence that lysosomal sequestration mediates daunorubicin resistance?

Altered intracellular distribution of weak base anticancer drugs owing to lysosomal sequestration is one purported mechanism contributing to chemotherapy resistance. This has often been demonstrated with the example of daunorubicin (DNR), chemotherapy with its characteristic red fluorescence used to trace it in cellular compartments. Here we addressed the question whether image analysis of DNR fluorescence can reflect its real intracellular distribution. We observed that the relationship between the intensity of the DNR fluorescence and its concentration in water solutions with or without proteins is far from linear. In contrast, nucleic acids, RNA and DNA in particular, dramatically diminish the DNR fluorescence, however, the intensity was proportional to the amount. Therefore, image analysis reflects the composition of different cell compartments (i.e., the presence of proteins and nucleic acids) rather than the actual concentration of DNR in these compartments. In line with these results, we observed highly fluorescent lysosomes and low fluorescent nucleus in sensitive cancer cells treated with low DNR concentrations, a fluorescence pattern thought to be found only in resistant cancer cells. Importantly, LC/MS/MS analysis of extracts from sensitive cells treated with DNR or DNR in combination with an inhibitor of vacuolar ATPase, concanamycin A, indicated that lysosomal accumulation of DNR increased with increasing extracellular concentration. However, even the highest lysosomal accumulation of DNR failed to reduce its extralysosomal concentration and thus change the cell sensitivity to the drug. In conclusion, our results strongly suggest that DNR fluorescence within cells does not indicate the real drug distribution. Further they suggested that lysosomal sequestration of DNR can hardly contribute to its resistance in cancer cells in vitro.

Stress and drug resistance in cancer

Patients diagnosed with cancer often undergo considerable psychological distress, and the induction of the psychological stress response has been linked with a poor response to chemotherapy. The psychological stress response is mediated by fluctuations of the hormones glucocorticoids (GCs) and catecholamines. Binding to their respective receptors, GCs and the catecholamines adrenaline/noradrenaline are responsible for signalling a wide range of processes involved in cell survival, cell cycle and immune function. Synthetic GCs are also often prescribed as co-medication alongside chemotherapy, and increasing evidence suggests that GCs may induce chemoresistance in multiple cancer types. In this review, we bring together evidence linking psychological stress hormone signalling with resistance to chemo- and immune therapies, as well as mechanistic evidence regarding the effects of exogenous stress hormones on the efficacy of chemotherapies.

A Unique Morphological Phenotype in Chemoresistant Triple-Negative Breast Cancer Reveals Metabolic Reprogramming and PLIN4 Expression as a Molecular Vulnerability

The major obstacle in successfully treating triple-negative breast cancer (TNBC) is resistance to cytotoxic chemotherapy, the mainstay of treatment in this disease. Previous preclinical models of chemoresistance in TNBC have suffered from a lack of clinical relevance. Using a single high dose chemotherapy treatment, we developed a novel MDA-MB-436 cell-based model of chemoresistance characterized by a unique and complex morphologic phenotype, which consists of polyploid giant cancer cells giving rise to neuron-like mononuclear daughter cells filled with smaller but functional mitochondria and numerous lipid droplets. This resistant phenotype is associated with metabolic reprogramming with a shift to a greater dependence on fatty acids and oxidative phosphorylation. We validated both the molecular and histologic features of this model in a clinical cohort of primary chemoresistant TNBCs and identified several metabolic vulnerabilities including a dependence on PLIN4, a perilipin coating the observed lipid droplets, expressed both in the TNBC-resistant cells and clinical chemoresistant tumors treated with neoadjuvant doxorubicin-based chemotherapy. These findings thus reveal a novel mechanism of chemotherapy resistance that has therapeutic implications in the treatment of drug-resistant cancer. IMPLICATIONS: These findings underlie the importance of a novel morphologic-metabolic phenotype associated with chemotherapy resistance in TNBC, and bring to light novel therapeutic targets resulting from vulnerabilities in this phenotype, including the expression of PLIN4 essential for stabilizing lipid droplets in resistant cells.

DNA primase polypeptide 1 (PRIM1) involves in estrogen-induced breast cancer formation through activation of the G2/M cell cycle checkpoint

The DNA primase polypeptide 1 (PRIM1) is responsible for synthesizing small RNA primers for Okazaki fragments generated during discontinuous DNA replication. PRIM1 mRNA expression levels in breast tumor samples were detected by real-time PCR analysis. Xenografted tumor model was established to study the carcinogenic role of PRIM1 and its potential therapeutic applications. The average PRIM1 mRNA (copy number × 10³ /μg) expression was 4.7-fold higher in tumors than in normal tissue (*p = 0.005, n = 254). PRIM1 was detected preferentially at a higher level (>40-fold) in poorly differentiated tumor tissues (n = 46) compared with more highly differentiated tumors tissues (n = 10) (*p = 0.005). Poor overall survival rate was correlated to the estrogen receptor positive (ER+, n = 20) patients with higher PRIM1 expression when compare to the ER- (n = 10) patients (Chi Square test, p = 0.03). Stable expression of PRIM1-siRNA in the ER+ BT-474 cells-xenograft tumors significantly reduced tumor volume in SCID mice (*p = 0.005). The anti-tumoral effects of inotilone isolated from Phellinus linteus was tested and had significant effects on the inhibition of PRIM1 protein expression in ER+ breast cancer cells. In vivo study was performed by administering inotilone (10 mg/kg, twice a week for 6 weeks), which resulted in significantly reduced BT-474-xenografted tumor growth volume compared with control (n =5 per group, *p < 0.05). This study provides evidences for the prognostic effects of PRIM1 with poor overall survival rate in the ER+ patients and will be valuable to test for therapeutic purpose.

Addressing Drug Resistance in Cancer with Macromolecular Chemotherapeutic Agents

Drug resistance to chemotherapeutics is a recurrent issue plaguing many cancer treatment regimens. To circumvent resistance issues, we have designed a new class of macromolecules as self-contained chemotherapeutic agents. The macromolecular chemotherapeutic agents readily self-assemble into well-defined nanoparticles and show excellent activity in vitro against multiple cancer cell lines. These cationic polymers function by selectively binding and lysing cancer cell membranes. As a consequence of this mechanism, they exhibit significant potency against drug-resistant cancer cells and cancer stem cells, prevent cancer cell migration, and do not induce resistance onset following multiple treatment passages. Concurrent experiments with the small-molecule chemotherapeutic, doxorubicin, show aggressive resistance onset in cancer cells, a lack of efficacy against drug-resistant cancer cell lines, and a failure to prevent cancer cell migration. Additionally, the polymers showed anticancer efficacy in a hepatocellular carcinoma patient derived xenograft mouse model. Overall, these results demonstrate a new approach to designing anticancer therapeutics utilizing macromolecular compounds.

Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer

Conventional cancer treatment strategies assume that maximum patient benefit is achieved through maximum killing of tumor cells. However, by eliminating the therapy-sensitive population, this strategy accelerates emergence of resistant clones that proliferate unopposed by competitors-an evolutionary phenomenon termed "competitive release." We present an evolution-guided treatment strategy designed to maintain a stable population of chemosensitive cells that limit proliferation of resistant clones by exploiting the fitness cost of the resistant phenotype. We treated MDA-MB-231/luc triple-negative and MCF7 estrogen receptor-positive (ER(+)) breast cancers growing orthotopically in a mouse mammary fat pad with paclitaxel, using algorithms linked to tumor response monitored by magnetic resonance imaging. We found that initial control required more intensive therapy with regular application of drug to deflect the exponential tumor growth curve onto a plateau. Dose-skipping algorithms during this phase were less successful than variable dosing algorithms. However, once initial tumor control was achieved, it was maintained with progressively smaller drug doses. In 60 to 80% of animals, continued decline in tumor size permitted intervals as long as several weeks in which no treatment was necessary. Magnetic resonance images and histological analysis of tumors controlled by adaptive therapy demonstrated increased vascular density and less necrosis, suggesting that vascular normalization resulting from enforced stabilization of tumor volume may contribute to ongoing tumor control with lower drug doses. Our study demonstrates that an evolution-based therapeutic strategy using an available chemotherapeutic drug and conventional clinical imaging can prolong the progression-free survival in different preclinical models of breast cancer.

Gene expression-based prognostic and predictive tools in breast cancer

Genomic assays measuring the expression of multiple genes have made their way into clinical practice and their utilization is now recommended by major international guidelines. A basic property of these tests is their capability to sub-divide patients into high- and low-risk cohorts thereby providing prognostic, and in certain settings, predictive decision support. Here, we summarize commercially available assays for breast cancer including RT-PCR and gene chip-based tests. Given the relative uncertainty in cancer treatment, multigene tests have the potential for a significant cost reduction as they can pinpoint those patients for whom chemotherapy proves to be unnecessary. However, concordance of risk assessment for an individual patient is still far from optimal. Additionally, emerging multigene approaches focus on predicting therapy response, which is a black spot of current tests. Promising techniques include the homologous recombination deficiency score, utilization of massive parallel sequencing to identify driver genes, employment of internet-based meta-analysis tools and investigation of miRNA expression signatures. Combination of multiple simultaneous analyses at diagnosis, including classical histopathological diagnostics, monogenic markers, genomic signatures and clinical parameters will most likely bring maximal benefit for patients. As the main driving force behind such genomic tests is the power to achieve cost reduction due to avoiding unnecessary systemic treatment, the future is most likely to hold a further proliferation of such assays.

Lanthionine synthetase C-like protein 2 (LanCL2) is a novel regulator of Akt

The serine/threonine protein kinase Akt controls a wide range of biochemical and cellular processes under the modulation of a variety of regulators. In this study, we identify the lanthionine synthetase C-like 2 (LanCL2) protein as a positive regulator of Akt activation in human liver cells. LanCL2 knockdown dampens serum- and insulin-stimulated Akt phosphorylation, whereas LanCL2 overexpression enhances these processes. Neither insulin receptor phosphorylation nor the interaction between insulin receptor substrate and phosphatidylinositide 3-kinase (PI3K) is affected by LanCL2 knockdown. LanCL2 also does not function through PP2A, a phosphatase of Akt. Instead, LanCL2 directly interacts with Akt, with a preference for inactive Akt. Moreover, we show that LanCL2 also binds to the Akt kinase mTORC2, but not phosphoinositide-dependent kinase 1. Whereas LanCL2 is not required for the Akt-mTORC2 interaction, recombinant LanCL2 enhances Akt phosphorylation by target of rapamycin complex 2 (mTORC2) in vitro. Finally, consistent with a function of Akt in regulating cell survival, LanCL2 knockdown increases the rate of apoptosis, which is reversed by the expression of a constitutively active Akt. Taken together, our findings reveal LanCL2 as a novel regulator of Akt and suggest that LanCL2 facilitates optimal phosphorylation of Akt by mTORC2 via direct physical interactions with both the kinase and the substrate.

Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis

Breast cancer research has paved the way of personalized oncology with the introduction of hormonal therapy and the measurement of estrogen receptor as the first widely accepted clinical biomarker. The expression of another receptor—HER2/ERBB2/neu—was initially a sign of worse prognosis, but targeted therapy has granted improved outcome for these patients so that today HER2 positive patients have better prognosis than HER2 negative patients. Later, the introduction of multigene assays provided the pathologists with an unbiased assessment of the tumors’ molecular fingerprint. The recent FDA approval of complete microarray pipelines has opened new possibilities for the objective classification of breast cancer samples. Here we review the applications of microarrays for determining ER and HER2 status, molecular subtypes as well as predicting prognosis and grade for breast cancer patients. An open question remains the role of single genes within such signatures. Openly available microarray datasets enable the execution of an independent cross-validation of new marker and signature candidates. In summary, we review the current state regarding clinical applications of microarrays in breast cancer molecular pathology.

Identifying resistance mechanisms against five tyrosine kinase inhibitors targeting the ERBB/RAS pathway in 45 cancer cell lines

Because of the low overall response rates of 10–47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort.

Proteomic approaches for investigation of therapy resistance in cancer

Resistance to anticancer therapy is a major obstacle for successful management of patients in oncology. Although in the past, various biological mechanisms involved in therapy resistance, in particular multidrug resistance, have been identified, cancer patients did not really benefit. The mechanisms include the enhanced activity of drug extrusion pumps, modulation of cellular death pathways, alteration and repair of target molecules and various other mechanisms. Together they build a complex network mediating an individual therapy-resistant phenotype. The improved description of this multifactorial network should be useful for prediction of treatment response and would allow to design an individual-tailored therapy regiment. Proteome analyzing technologies appear as powerful tools for identifying new factors and protein expression profiles associated with anticancer therapy resistance. In the last years, the application of proteomic techniques identified multiple new factors or protein expression signatures in drug-resistant cell models and cancerous tissues. However, the functional role and the clinical impact of these findings are not yet clarified. So far, none of the proteomic data were useful for the development of improved diagnostic tests, for prediction of individual therapy response or for development of updated chemosensitizers. Here, the previous therapy resistance-related proteome data and future perspectives will be discussed.

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.

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.

Discovery of IL-18 as a novel secreted protein contributing to doxorubicin resistance by comparative secretome analysis of MCF-7 and MCF-7/Dox

Background

Resistance to chemotherapy is the major cause of failure in breast cancer treatment. Recent studies suggest that secreted proteins may play important roles in chemoresistance. We sought to systematically characterize secreted proteins associated with drug resistance, which may represent potential serum biomarkers or novel drug targets.

Methodology/Principal Findings

In the present work, we adopted the proteomic strategy of one-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to compare the secretome of MCF-7 and doxorubicin-resistant MCF-7/Dox. A total of 2,084 proteins were identified with at least two unique peptides in the conditioned media of two cell lines. By quantification with label-free spectral counting, 89 differentially expressed secreted proteins (DESPs) between the two cell lines were found. Among them, 57 DESPs were first found to be related to doxorubicin resistance in this work, including 24 extracellular matrix related proteins, 2 cytokines and 31 unclassified proteins. We focused on 13 novel DESPs with confirmed roles in tumor metastasis. Among them, the elevated expression of IL-18 in doxorubicin-resistant cell lines and breast tumor tissues was validated and its role in doxorubicin resistance was further confirmed by cell viability experiments in the presence or absence of this protein.

Conclusions/Significance

Comparative analysis of the secretome of MCF-7 and MCF-7/Dox identified novel secreted proteins related to chemotherapy resistance. IL-18 was further validated to contribute to doxorubicin resistance, in addition to its confirmed role in breast cancer metastasis. Due to its dual roles in both drug resistance and tumor metastasis, IL-18 may represent a useful drug target for breast cancer therapy.

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

In the last decade, the development of microarrays and the ability to perform massively parallel gene expression analysis of human tumours were received with great excitement by the scientific community. The promise of microarrays was of apocalyptic dimensions, with some experts envisaging that it would be a matter of a few years for this technology to replace traditional clinicopathological markers in clinical practice and treatment decision-making. The replacement of histopathology by high-tech and more objective approaches to cancer diagnosis, prognostication and prediction was, at that time, a foregone conclusion. Ten years after the initial publications of translational research studies using microarrays, one cannot deny that this technology has changed the way breast cancer is perceived. It has brought the concept of breast cancer heterogeneity to the forefront of cancer research, and the fact that distinct subtypes of breast cancer are completely different diseases that affect the same anatomical site. Furthermore, it has led to the development of prognostic and predictive 'gene signatures', which are yet to be fully incorporated into clinical practice. Importantly, though, the prognostic and predictive power of microarrays has been shown to be complementary to, rather than a replacement for, traditional clinicopathological parameters. Here we endeavour to provide a fair and balanced assessment of what microarray-based gene expression analysis has taught us in the last decade and its contribution to breast cancer classification, prognostication and prediction.

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

Adjuvant chemotherapy for breast cancer after surgery has effectively lowered metastatic recurrence rates. However, a considerable proportion of women suffer recurrent cancer at distant metastatic sites despite adjuvant treatment. Identification of the genes crucial for tumor response to specific chemotherapy drugs is a challenge but is necessary to improve outcomes. By using integrated genomics, we identified a small number of overexpressed and amplified genes from chromosome 8q22 that were associated with early disease recurrence despite anthracycline-based adjuvant chemotherapy. We confirmed the association in an analysis of multiple independent cohorts. SiRNA-mediated knockdown of either of two of these genes, the antiapoptotic gene YWHAZ and a lysosomal gene LAPTM4B, sensitized tumor cells to anthracyclines, and overexpression of either of the genes induced anthracycline resistance. Overexpression of LAPTM4B resulted in sequestration of the anthracycline doxorubicin, delaying its appearance in the nucleus. Overexpression of these two genes was associated with poor tumor response to anthracycline treatment in a neoadjuvant chemotherapy trial in women with primary breast cancer. Our results suggest that 8q22 amplification and overexpression of LAPTM4B and YWHAZ contribute to de novo chemoresistance to anthracyclines and are permissive for metastatic recurrence. Overexpression of these two genes may predict anthracycline resistance and influence selection of chemotherapy.

PSMB7 is associated with anthracycline resistance and is a prognostic biomarker in breast cancer

BACKGROUND

To date individual markers have failed to correctly predict resistance against anticancer agents in breast cancer. We used gene expression patterns attributable to chemotherapy-resistant cells to detect potential new biomarkers related to anthracycline resistance. One of the genes, PSMB7, was selected for further functional studies and clinical validation.

METHODS

We contrasted the expression profiles of four pairs of different human tumour cell lines and of their counterparts resistant to doxorubicin. Observed overexpression of PSMB7 in resistant cell lines was validated by immunohistochemistry. To examine its function in chemoresistance, we silenced the gene by RNA interference (RNAi) in doxorubicin-resistant MCF-7 breast cancer cells, then cell vitality was measured after doxorubicin treatment. Microarray gene expression from GEO raw microarray samples with available progression-free survival data was downloaded, and expression of PSMB7 was used for grouping samples.

RESULTS

After doxorubicin treatment, 79.8+/-13.3% of resistant cells survived. Silencing of PSMB7 in resistant cells decreased survival to 31.8+/-6.4% (P>0.001). A similar effect was observed after paclitaxel treatment. In 1592 microarray samples, the patients with high PSMB7 expression had a significantly shorter survival than the patients with low expression (P<0.001).

CONCLUSION

Our findings suggest that high PSMB7 expression is an unfavourable prognostic marker in breast cancer.

Altered expression of proliferation-inducing and proliferation-inhibiting genes might contribute to acquired doxorubicin resistance in breast cancer cells

This study was designed to investigate the molecular changes that may develop during exposure of breast cancer cells to anticancer agents and that may lead to acquired resistance. We used two breast cancer cell lines, a parental (MCF7/WT) and a doxorubicin-resistant (MCF7/DOX) one. Cell survival, cell cycle distribution and RT-PCR expression level of genes involved in DNA damage response, MDR1, GST and TOPOIIalpha were measured. MCF7/DOX cells were five-fold more resistant to doxorubicin (DOX) than the MCF7/WT cells. DOX treatment causes arrest of MCF7/DOX cells in G1 and G2 phases of cell cycle whereas MCF7/WT cells were arrested in S-phase. The molecular changes in both cell lines due to DOX treatment could be classified into: (1) the basal level of p53, p21, BRCA1, GST and TOPOIIalpha mRNA was higher in MCF7/DOX than MCF7/WT. During DOX treatment, the expression level of these genes decreased in both cell lines but the rate of down-regulation was faster in MCF7/WT than MCF7/DOX cells. (2) The expression level of MDR1 was the same in both cell lines but 48 and 72 h of drug treatment, MDR1 disappeared in MCF7/WT but still expressed in MCF7/DOX. (3) There was no change in the expression level of BAX, FAS and BRCA2 in both cell lines. Conclusively, after validation in clinical samples, overexpression of genes like BRCA1, p53, p21, GST, MDR1 and TOPOIIalpha could be used as a prognostic biomarker for detection of acquired resistance in breast cancer and as therapeutic targets for the improvement of breast cancer treatment strategies.

Radiogenomics: creating a link between molecular diagnostics and diagnostic imaging

Studies employing high-throughput biological techniques have recently contributed to an improved characterization of human cancers, allowing for novel sub-classification, better diagnostic accuracy, and more precise prognostication. However, requirement of surgical procurement of tissue among other things limits the clinical application of such methods in everyday patient care. Radiographic imaging is routine in clinical practice but is currently histopathology based. The use of routine radiographic imaging provides a potential platform for linking specific imaging traits with specific gene expression patterns that inform the underlying cellular pathophysiology; imaging features could then serve as molecular surrogates that contribute to the diagnosis, prognosis, and likely gene-expression-associated treatment response of various forms of human cancer. This review focuses on high-throughput methods such as microarray analysis of gene expression, their role in cancer research, and in particular, on novel methods of associating gene expression patterns with radiographic imaging phenotypes, known as "radiogenomics." These findings underline a potential future role of both diagnostic and interventional radiologists in genetic assessment of cancer patients with radiographic imaging studies.

Gene expression profiling of breast cancer

DNA microarray platforms for gene expression profiling were invented relatively recently, and breast cancer has been among the earliest and most intensely studied diseases using this technology. The molecular signatures so identified help reveal the biologic spectrum of breast cancers, provide diagnostic tools as well as prognostic and predictive gene signatures, and may identify new therapeutic targets. Data are best presented in an open access format to facilitate external validation, the most crucial step in identifying robust, reproducible gene signatures suitable for clinical translation. Clinically practical applications derived from full expression profile studies already in use include reduced versions of microarrays representing key discriminatory genes and therapeutic targets, quantitative polymerase chain reaction assays, or immunohistochemical surrogate panels (suitable for application to standard pathology blocks). Prospective trials are now underway to determine the value of such tools for clinical decision making in breast cancer; these efforts may serve as a model for using such approaches in other tumor types.

Utilization of genomic signatures to direct use of primary chemotherapy

The success of treatment of cancer patients depends on matching the most effective therapeutic regimen with the characteristics of the individual patient, balancing benefit against risk of adverse events. The primary challenge in achieving this goal is the heterogeneity of the disease, recognizing that breast, lung, colon and other cancers are not single diseases but rather an array of disorders with distinct molecular mechanisms. Genomic analyses, and in particular gene expression profiling, has been shown to have the capacity to dissect this heterogeneity and afford opportunities to match therapies with the characteristics of the individual patient's tumor. Here we review the success in developing gene expression signatures that have the capability of predicting response to various commonly used and newly developing cancer therapeutics. We further discuss the challenges and the opportunities in utilizing these tools in present-day clinical practice.

MDM2 antagonist nutlin-3 is a potent inducer of apoptosis in pediatric acute lymphoblastic leukemia cells with wild-type p53 and overexpression of MDM2

In pediatric acute lymphoblastic leukemia (ALL), overexpression of murine double minute 2 (MDM2) protein by leukemic cells is typically associated with a wild-type (wt)-p53 phenotype and chemoresistance. A recently developed small-molecule antagonist of MDM2, nutlin-3, inhibits the MDM2-p53 interaction, resulting in induction of p53 activity and apoptosis. In this study, we evaluated the cytotoxic effect of nutlin-3 on ALL cells with different p53 status and MDM2 expression, using 18 cell lines and 30 primary leukemia samples. We found that both ALL cell lines and primary ALL samples with wt-p53 are sensitive to nutlin-3. No cytotoxic effect of nutlin-3 was detected in ALL cells with either p53-mutant or -null phenotype. In wt-p53 ALL cells, there was a significant positive correlation between MDM2 expression levels and sensitivity to nutlin-3. Nutlin-3-induced cell death was mediated by p53-induced activation of proapoptotic proteins and by p53-induced repression of the anti-apoptotic protein survivin. As p53 function is inhibited by MDM2 in chemoresistant, MDM2-overexpressing ALL cells, potent killing of these cells by nutlin-3 suggests that this agent may be a novel therapeutic for refractory ALL.

Gene expression patterns within cell lines are predictive of chemosensitivity

Background

The NCI has undertaken a twenty-year project to characterize compound sensitivity patterns in a selected set of sixty tumor derived cell lines. Previous studies have explored the relationship between compound sensitivity patterns to gene expression, protein expression, and DNA copy number for these same cell lines. A strong correlation between the pattern of expression of a biomarker and sensitivity to a compound could suggest a clinically interesting biological relationship between the two.

Results

We isolated RNA's and measured expression of 40000 genes using cDNA microarrays from the fifty-nine publicly available cell lines. Analysis of this data set in comparison with published gene expression data sets demonstrates a high degree of reproducibility in expression level measurements even using completely independent RNA preparations and array technologies. Using the fifty-nine cell lines for discovery and an additional seven cell lines for which extensive compound sensitivity data were available as a test set, we determined that gene-compound pairs with a correlation coefficient above 0.6 had a false discovery rate of approximately 5%. Large scale features of the gene expression and chemosensitivity data, such as tissue of origin and other physiological factors, did not seem to explain the majority of correlations between gene and compound patterns.

Conclusion

A comparison of gene expression and compound sensitivity in panels of cell lines was demonstrated to have a relatively high validation and low false discovery rate supporting the use of this approach and datasets for identifying candidate biomarkers and targeted biologically active compounds.

Connecting chemosensitivity, gene expression and disease

Omics-based investigations offer potentially powerful readouts that might be useful for probing the underlying biology of normal and diseased states, identifying novel therapeutic targets and proposing relevant markers for designing treatment strategies. A vital component of these investigations involves a systematic analysis of gene expression and chemosensitivity data in the context of disease states and small molecule probes into the function of targets responsible for a disease phenotype. Systematic analysis of chemical and pharmacogenetics data offers a possible means to identify novel, small-molecule, potentially therapeutic, agents that affect the phenotype of a particular target. Elegantly simple in concept, the covariation of genetic and chemosensitivity readouts provide a hypothetical link for relating compounds through genomic expression profiles to underlying biology.

Dissociation of gemcitabine sensitivity and protein kinase B signaling in pancreatic ductal adenocarcinoma models

OBJECTIVE

To understand the impact of protein kinase B (PKB; Akt) signaling on growth and protection from apoptosis in pancreatic ductal adenocarcinoma models demonstrating differences in PKB activity.

METHODS

Gemcitabine sensitivity was investigated in a panel of cell lines, characterized by differences in levels of activated PKB. Suppression of PKB activity was achieved with an inhibitor of phosphatidylinositol 3-kinase (wortmannin) and silencing RNA.

RESULTS

Enhanced gemcitabine (2',2'-difluoro-2'-deoxycytidine)-induced cytotoxicity in vitro was achieved with suppression of high PKB activity with wortmannin in BxPC-3, PK-1, and PK-8 cells and silencing RNA targeted to total PKB, rather than PKBbeta, in PANC-1 cells. Opposite to gemcitabine sensitivity levels in vitro, the growth of PANC-1 xenografts was inhibited with gemcitabine treatment, whereas BxPC-3 became drug resistant. Monolayer cell cultures reestablished from solid tumors behaved similarly to original cultures, suggesting that the tumor microenvironment has a critical role in determining drug sensitivity. A comparison of transcript profiles of the models indicated that PKB signaling might be modulated by a number of pathways responsive to the tumor hypoxia microenvironment.

CONCLUSIONS

These results suggested that gemcitabine efficacy involving the PKB pathway depends on PKB activity, its mechanisms of enhanced activity, as well as its function in a signaling network.

Establishment of in-vitro models of chemotherapy resistance

Chemotherapy resistance is one of the most prevalent obstacles to the treatment of cancer, resulting in increased mortality and prolonged exposure to cytotoxic agents with no treatment benefit. One of the tools utilized in the study of mechanisms of chemotherapy resistance are established cell lines derived from human neoplasms. These cell lines can be challenged in vitro with controlled chemotherapy doses to produce chemotherapy-resistant variants. Analysis of these novel chemotherapy-resistant cell lines may then identify genetic and proteomic changes which are associated with the resistant phenotype. Two very important mediators of chemotherapy resistance (P-glycoprotein and multidrug resistance protein-1) were initially identified in chemotherapy-resistant cell lines. To make these in-vitro studies clinically relevant it is, however, necessary to duplicate as far as possible the treatment conditions used in vivo. Considerations should include clinically relevant drug concentrations, such as those derived from peak plasma values, and the type of treatment schedule to be employed.

Predictive medicine: incipient reality or fata morgana?

The success of targeted therapy depends on reliable biomarkers that indicate the presence and accessibility of the target molecules with which the therapeutic drug will interact. In principle, this is independent of whether the drug is a small molecule, such as kinase inhibitors, or a therapeutic antibody, such as trastuzumab or cetuximab. The functional system of target-drug interaction is described as 'predictive medicine', one of the great hopes in the treatment of cancer. The major challenges are the precise prediction of the patient's individual prognosis, of the probability of metastases, and of individual therapeutic response. The questions, challenges, and possible answers related to this complex issue as well as the prerequisites for the development of more efficient and less toxic cancer therapy are discussed.

Radiogenomic analysis to identify imaging phenotypes associated with drug response gene expression programs in hepatocellular carcinoma

PURPOSE

To determine whether conventional contrast-enhanced computed tomography (CT) could be used to identify imaging phenotypes associated with a doxorubicin drug response gene expression program in hepatocellular carcinoma (HCC) by using an integrated imaging-genomic approach.

MATERIALS AND METHODS

Thirty HCCs were analyzed and scored individually across six predefined imaging phenotypes. Unsupervised and supervised bioinformatics analyses were performed to correlate the imaging scores with the corresponding tumor microarray data (each microarray contained gene expression measurements across approximately 18,000 genes) to identify relationships between the imaging traits and underlying tumor gene expression. Enrichment for a predefined doxorubicin-response gene expression program was then performed against the imaging phenotype-associated genes and enrichment determined.

RESULTS

An imaging phenotype related to tumor margins on arterial phase images demonstrated significant correlation with the doxorubicin-response transcriptional program (P < .05, q < 0.1). It was also significantly associated with HCC venous invasion and tumor stage (P < .05, q < 0.1). Tumors with higher tumor margin scores were more strongly associated with the doxorubicin resistance transcriptional program and had a greater prevalence of venous invasion and worse stage. Tumors with lower tumor margin scores, however, demonstrated a converse relationship.

CONCLUSIONS

It is possible to identify HCC imaging phenotypes at CT that correlate with a doxorubicin drug response gene expression program. Given the role of doxorubicin in regional therapies for HCC management, it is possible that such an approach could be used to guide HCC therapy on a tumor-by-tumor basis on the basis of underlying tumor gene expression patterns.

Resistance-associated signatures in breast cancer

A major obstacle in the treatment of breast cancer is the lack of adequate methods for predicting patient response to a particular chemotherapy regime. To date, single tumour markers have provided limited success. DNA array technologies identifying thousands of genes simultaneously can help to solve this problem. We investigated cancer cell lines sensitive and resistant to the topoisomerase inhibitors doxorubicin and mitoxantrone. These drugs are used in several different breast cancer treatment protocols. We have identified the top genes best associated with resistance against each cytostatic agent. We applied our gene expression signatures to a set of pre-characterised patients receiving doxorubicin monotherapy. The patients classified as sensitive to chemotherapy exhibited longer survival than the resistant ones. In summary, in our study we have successfully transferred experimental results to a clinical problem, and managed to perform a predictive test for a selected monotherapy protocol. However, many different studies have been performed using microarrays, each producing a different gene list for the same classification problem. It is likely that future diagnostic tools will include the results of several different laboratories, focus on genes validated on different technological platforms and use large cohorts of patients.

Gene expression profiles as biomarkers for the prediction of chemotherapy drug response in human tumour cells

Genome profiling approaches such as cDNA microarray analysis and quantitative reverse transcription polymerase chain reaction are playing ever-increasing roles in the classification of human cancers and in the discovery of biomarkers for the prediction of prognosis in cancer patients. Increasing research efforts are also being directed at identifying set of genes whose expression can be correlated with response to specific drugs or drug combinations. Such genes hold the prospect of tailoring chemotherapy regimens to the individual patient, based on tumour or host gene expression profiles. This review outlines recent advances and challenges in using genome profiling for the identification of tumour or host genes whose expression correlates with response to chemotherapy drugs both in vitro and in clinical studies. Genetic predictors of response to a variety of anticancer agents are discussed, including the anthracyclines, taxanes, topoisomerase I and II inhibitors, nucleoside analogs, alkylating agents, and vinca alkaloids.

Comparative gene expression analysis of a chronic myelogenous leukemia cell line resistant to cyclophosphamide using oligonucleotide arrays and response to tyrosine kinase inhibitors

Acquired imatinib resistance in chronic myelogenous leukemia (CML) can be the consequence of mutations in the kinase domain of BCR-ABL or increased protein levels. However, as in other malignancies, acquired resistance to cytostatic drugs is a common reason for treatment failure or disease progression. As a model for drug resistance, we developed a CML cell line resistant to cyclophosphamide (CP). Using oligonucleotide arrays, we examined changes in global gene expression. Selected genes were also examined by real-time PCR and flow cytometry. Neither the parent nor the resistant lines had mutations in their ATP binding domain. Filtering genes with a low-base line expression, a total of 239 genes showed significant changes (162 up- and 77 down-regulated) in the resistant clone. Most of the up-regulated genes were associated with metabolism, signal transduction, or encoded enzymes. The gene for aldehyde dehydrogenase 1 was over-expressed more than 2000-fold in the resistant clone. BCR-ABL was expressed in both cell lines to a comparable extent. When exposed to the tyrosine kinase inhibitors imatinib and nilotinib, both lines were sensitive. In conclusion, we found multiple genetic changes in a CML cell line resistant to CP related to metabolism, signal transduction or apoptosis. Despite these changes, the resistant cells retained sensitivity to tyrosine kinase inhibitors.

Integrating large-scale genotype and phenotype data

With the completion of the Human Genome Project, a new emphasis is focusing on the sequence variation and the resulting phenotype. The number of data available from genomic studies addressing this relationship is rapidly growing. In order to analyze these data as a whole, they need to be integrated, aggregated and annotated in a timely manner. The Pharmacogenetics and Pharmacogenomics Knowledge Base PharmGKB; (<www.pharmgkb.org>) assembles and disseminates these data and their associated metadata that are needed for unambiguous identification and replication. Assembling these data in a timely manner is challenging, and the scalability of these data produce major challenges for a knowledge base such as PharmGKB. However, it is only through rapid global meta-annotation of these data that we will understand the relationship between specific genotype(s) and the related phenotype. PharmGKB has confronted these challenges, and these experiences and solutions can benefit all genome communities.