Quantitative proteome analysis of multidrug resistance in human ovarian cancer cell line

Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.

Quantitative proteomics characterization of cancer biomarkers and treatment

Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the poor correlation between genes and proteins. Quantitative proteomics, capable of quantifying the relatively different protein abundance in cancer patients, has been increasingly adopted in cancer research. Quantitative proteomics has great application potentials, including cancer diagnosis, personalized therapeutic drug selection, real-time therapeutic effects and toxicity evaluation, prognosis and drug resistance evaluation, and new therapeutic target discovery. In this review, the development, testing samples, and detection methods of quantitative proteomics are introduced. The biomarkers identified by quantitative proteomics for clinical diagnosis, prognosis, and drug resistance are reviewed. The challenges and prospects of quantitative proteomics for personalized medicine are also discussed.

PKM2 Expression as Biomarker for Resistance to Oxaliplatin-Based Chemotherapy in Colorectal Cancer

The purpose of the current study is to investigate the prognostic significance of M2 isoform of pyruvate kinase (PKM2) mRNA expression loss in patients with operable colon cancer (CC). Two hundred sixty-two specimens from patients with stage-III or high-risk stage-II CC (group-A) treated with adjuvant fluoropyrimidine and oxaliplatin chemotherapy (FOLFOX), 118 specimens from metastatic CC patients (group-B) treated with FOLFOX, and 104 metastatic CC patients (group-C) treated with irinotecan-based chemotherapy were analyzed for PKM2, TS, ERCC1, MYC, and NEDD9 mRNA expression, as well as KRAS exon2 and BRAF^V600E mutations. High PKM2 mRNA expression was correlated with left-sided located primaries (p = 0.001, group-A; p = 0.003, group-B; p = 0.001, group-C), high-grade tumors (p = 0.001, group-A; p = 0.017, group-B; p = 0.021, group-C), microsatellite-stable tumors (p < 0.001, group-A), pericolic lymph nodes involvement (p = 0.018, group-A), and cMYC mRNA expression (p = 0.002, group-A; p = 0.008, group-B; p = 0.006, group-C). High PKM2 mRNA expression was correlated with significantly lower disease free survival (DFS) (p = 0.002) and overall survival (OS) (p = 0.001) in the group-A. Similarly, PKM2 mRNA expression was associated with significantly decreased progression free survival (PFS) (p = 0.001) and OS (p = 0.001) in group-B. On the contrary, no significant association for the PKM2 mRNA expression has been observed with either PFS (p = 0.612) or OS (p = 0.517) in group-C. To conclude, the current study provides evidence for the prediction of PKM2 mRNA expression oxaliplatin-based treatment resistance.

Chemotherapy Resistance in Advanced Ovarian Cancer Patients

Ovarian cancer is the seventh most common gynaecologic malignancy seen in women. Majority of the patients with ovarian cancer are diagnosed at the advanced stage making prognosis poor. The standard management of advanced ovarian cancer includes tumour debulking surgery followed by chemotherapy. Various types of chemotherapeutic regimens have been used to treat advanced ovarian cancer, but the most promising and the currently used standard first-line treatment is carboplatin and paclitaxel. Despite improved clinical response and survival to this combination of chemotherapy, numerous patients either undergo relapse or succumb to the disease as a result of chemotherapy resistance. To understand this phenomenon at a cellular level, various macromolecules such as DNA, messenger RNA and proteins have been developed as biomarkers for chemotherapy response. This review comprehensively summarizes the problem that pertains to chemotherapy resistance in advanced ovarian cancer and provides a good overview of the various biomarkers that have been developed in this field.

Mass spectrometry-based proteomics techniques and their application in ovarian cancer research

Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.

Differentially expressed and survival-related proteins of lung adenocarcinoma with bone metastasis

Despite recent advances in targeted and immune‐based therapies, the poor prognosis of lung adenocarcinoma (LUAD) with bone metastasis (BM) remains a challenge. First, two‐dimensional gel electrophoresis (2‐DE) was used to identify proteins that were differentially expressed in LUAD with BM, and then matrix‐assisted laser desorption/ionization time of flight mass spectrometry (MALDI‐TOF‐MS) was used to identify these proteins. Second, the Cancer Genome Atlas (TCGA) was used to identify mutations in these differentially expressed proteins and Kaplan–Meier plotter (KM Plotter) was used to generate survival curves for the analyzed cases. Immunohistochemistry (IHC) was used to check the expression of proteins in 28 patients with BM and nine patients with LUAD. Lastly, the results were analyzed with respect to clinical features and patient's follow‐up. We identified a number of matched proteins from 2‐DE. High expression of enolase 1 (ENO1) (HR = 1.67, logrank P = 1.9E‐05), ribosomal protein lateral stalk subunit P2 (RPLP2) (HR = 1.77, logrank P = 2.9e‐06), and NME/NM23 nucleoside diphosphate kinase 2 (NME1‐NME2) (HR = 2.65, logrank P = 3.9E‐15) was all significantly associated with poor survival (P < 0.05). Further, ENO1 was upregulated (P = 0.0004) and calcyphosine (CAPS1) was downregulated (P = 5.34E‐07) in TCGA LUAD RNA‐seq expression data. IHC revealed that prominent ENO1 staining (OR = 7.5, P = 0.034) and low levels of CAPS1 (OR = 0.01, P < 0.0001) staining were associated with BM incidence. Finally, we found that LUAD patients with high expression of ENO1 and RPLP2 had worse overall survival. This is the first instance where the genes ENO1, RPLP2, NME1‐NME2 and CAPS1 were associated with disease severity and progression in LUAD patients with BM. Thus, with this study, we have identified potential biomarkers and therapeutic targets for this disease.

Hypoxia Pathway Proteins As Central Mediators of Metabolism in the Tumor Cells and Their Microenvironment

Low oxygen tension or hypoxia is a determining factor in the course of many different processes in animals, including when tissue expansion and cellular metabolism result in high oxygen demands that exceed its supply. This is mainly happening when cells actively proliferate and the proliferating mass becomes distant from the blood vessels, such as in growing tumors. Metabolic alterations in response to hypoxia can be triggered in a direct manner, such as the switch from oxidative phosphorylation to glycolysis or inhibition of fatty acid desaturation. However, as the modulated action of hypoxia-inducible factors or the oxygen sensors (prolyl hydroxylase domain-containing enzymes) can also lead to changes in enzyme expression, these metabolic changes can also be indirect. With this review, we want to summarize our current knowledge of the hypoxia-induced changes in metabolism during cancer development, how they are affected in the tumor cells and in the cells of the microenvironment, most prominently in immune cells.

Identification of DJ-1 as a contributor to multidrug resistance in human small-cell lung cancer using proteomic analysis

Proteomic approaches have been proven to provide an important tool in identifying drug resistance-associated proteins. The aim of this study was to investigate the protein profiling of drug resistance-related proteins in small-cell lung cancer (SCLC) by proteomic analysis. The proteomic profiling was performed by two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) coupled with MALDI-TOF-TOF of SCLC in the multidrug-resistant cell line H69AR and its parental cell line H69. A total of 11 proteins were identified to be >2-fold up-or downregulated between the two cell lines. DJ-1, one of the differently expressed proteins identified by proteomics, was further examined by immunohistochemistry staining in 116 cases of SCLC tissues. Immunohistochemical results demonstrated that DJ-1 was expressed in 51.7% (60/116) of SCLC. DJ-1 expression was correlated significantly with survival time of SCLC patients (P < 0.05), but not with other clinical parameters such as gender, age and clinical stage (P > 0.05). Downregulation of DJ-1 using DJ-1-siRNA in H69AR cells sensitized cancer cells to chemotherapeutic drugs through increasing drug-induced cell apoptosis accompanied with G0-G1 phase arrest. These findings suggest DJ-1 may serve as a potential biomarker for chemoresistance and prognostic factor for patients with SCLC.

Targeting Lung Cancer Stem Cells: Research and Clinical Impacts

Lung cancer is the most common cancer worldwide, accounting for 1.8 million new cases and 1.6 million deaths in 2012. Non-small cell lung cancer (NSCLC), which is one of two types of lung cancer, accounts for 85–90% of all lung cancers. Despite advances in therapy, lung cancer still remains a leading cause of death. Cancer relapse and dissemination after treatment indicates the existence of a niche of cancer cells that are not fully eradicated by current therapies. These chemoresistant populations of cancer cells are called cancer stem cells (CSCs) because they possess the self-renewal and differentiation capabilities similar to those of normal stem cells. Targeting the niche of CSCs in combination with chemotherapy might provide a promising strategy to eradicate these cells. Thus, understanding the characteristics of CSCs has become a focus of studies of NSCLC therapies.

Knockdown of the M2 Isoform of Pyruvate Kinase (PKM2) with shRNA Enhances the Effect of Docetaxel in Human NSCLC Cell Lines In Vitro

PURPOSE

The aim of our study was to explore the relationships between the M2 isoform of pyruvate kinase (PKM2) and the sensitivity of human non-small cell lung cancer (NSCLC) cells to docetaxel in vitro.

MATERIALS AND METHODS

With the method of plasmid transfection, we silenced the expression of PKM2 successfully in A549 and H460 cells. Western blotting and real-time PCR were applied to detect PKM2 expression at protein and gene levels. Cell viability was examined by CCK8 assay. Cell cycle distribution and apoptosis were examined by flow cytometry. P21 and Bax were detected.

RESULTS

Expression of PKM2 mRNA and protein were significantly decreased by shRNA targeting PKM2. Silencing of PKM2 increased docetaxel sensitivity of human NSCLC A549 and H460 cells in a collaborative manner, resulting in strong suppression of cell viability. The results of flow cytometric assays suggested that knockdown of PKM2 or docetaxel treatment, whether used singly or in combination, blocked the cells in the G2/M phase, which is in consistent with the effect of the two on the expression of p21. Cells with PKM2 silencing were more likely to be induced into apoptosis by docetaxel although knockdown of PKM2 alone can't induce apoptosis significantly, which is in consistent with the effect of the two on Bax expression.

CONCLUSION

The results suggest that PKM2 knockdown could serve as a chemosensitizer to docetaxel in non-small lung cancer cells through targeting PKM2, leading to inhibition of cell viability, increase of cell arrest of G2/M phase and apoptosis.

PKM2 enhances chemosensitivity to cisplatin through interaction with the mTOR pathway in cervical cancer

Pyruvate kinase M2 (PKM2) is a key driver of aerobic glycolysis in cancer cells and has been shown to be up-regulated by mTOR in vitro. Our previous proteomic profiling studies showed that PKM2 was significantly upregulated in cervical cancer tissues after treatment with neoadjuvant chemotherapy (NACT). Whether PKM2 expression predicts cisplatin-based NACT sensitivity and is mTOR dependent in cervical cancer patients remains unclear. Using paired tumor samples (pre- and post-chemotherapy) from 36 cervical cancer patients, we examined mTOR, HIF-1α, c-Myc, and PKM2 expression in cervical cancer samples and investigated the response to cisplatin-based NACT. In addition, we established PKM2 suppressed cervical cancer cell lines and evaluated their sensitivity to cisplatin in vitro. We found that the mTOR/HIF-1α/c-Myc/PKM2 signaling pathway was significantly downregulated in post-chemotherapy cervical cancer tissues. High levels of mTOR, HIF-1α, c-Myc, and PKM2 were associated with a positive chemotherapy response in cervical cancer patients treated with cisplatin-based NACT. In vitro, PKM2 knockdown desensitized cervical cancer cells to cisplatin. Moreover, PKM2 had complex interactions with mTOR pathways. mTOR, HIF1α, c-Myc, and PKM2 expression in cervical cancer may serve as predictive biomarkers to cisplatin-based chemotherapy. PKM2 enhances chemosensitivity to cisplatin through interaction with the mTOR pathway in cervical cancer.

Proteomics of ovarian cancer: functional insights and clinical applications

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics' contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. We propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.

High Expression of Pyruvate Kinase M2 is Associated with Chemosensitivity to Epirubicin and 5-Fluorouracil in Breast Cancer

BACKGROUND

Pyruvate kinase M2 (PKM2) is the key enzyme in the Warburg effect, and it was recently reported to be involved in the metabolic pathways of chemotherapeutic drugs. However, the role of PKM2 in breast cancer and its influence in the sensitivity to front-line anticancer drugs remains unclear.

METHODS

In this study, we examined the correlation between the expression of PKM2 and the sensitivity of primary breast cancer cells to anticancer drugs. PKM2 expression was studied by immunohistochemistry using biopsy samples of 296 patients diagnosed with invasive breast carcinoma, and the collagen gel droplet embedded culture-drug sensitivity tests (CD-DST) was conducted to all the patients to detect in vitro chemosensitivity after surgery.

RESULTS

We found high PKM2 expression was significantly associated with in vitro chemosensitivity to epirubicin (EPI) (P=0.019) and 5-fluorouracil (5-Fu) (P=0.009) in breast cancer patients. Then we used a small group of neoadjuvant chemotherapy cases to confirm that the higher PKM2 expression, the better pathological response to therapy was obtained in patients treated with EPI-based or EPI plus 5-Fu chemotherapy regimens. Although univariate and multivariate analysis indicated that high PKM2 was a poor independent predictor of progression free survival (PFS) and overall survival (OS) in breast cancer, patients with PKM2 high expression who received EPI-based or EPI plus 5-Fu chemotherapy were found to have a longer PFS (P=0.003, P=0.013) and OS (P=0.003, P=0.004) than patients treated with non-EPI/5-Fu-based regimens, respectively.

CONCLUSIONS

Our findings confirmed the poor prognosis of high PKM2 expression in breast cancer patients and revealed the predictive value of high PKM2 in the therapeutic response to EPI and 5-Fu. Moreover, our results provide the guidance of individual treatment for breast cancer patients who are foreboded a poor prognosis by the presence of high PKM2 status.

Metabolic markers GAPDH, PKM2, ATP5B and BEC-index in advanced serous ovarian cancer

Background

A deregulated energy metabolism is a hallmark of malignant disease that offers possible future targets for treatment. We investigated the prognostic value of the glycolytic enzymes glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and pyruvate kinase type M2 (PKM2), mitochondrial β-F1-ATPase (ATP5B) and the bioenergetic cellular (BEC) index in advanced ovarian cancer.

Methods

Fresh tumor samples were prospectively collected from 123 patients undergoing primary surgery for suspected advanced ovarian cancer. Of these, 57 met the eligibility criteria; stage IIC-IV, serous or endometrioid subtype, specimens containing ≥ 50% tumor cells and patients receiving platinum-based chemotherapy. An adequate amount of mRNA could be extracted in all but one case, with a resultant study population of 56 patients. Eighty-six percent of cases had serous tumors, and 93% were grade 2–3. GAPDH, PKM2 and ATP5B mRNA- and protein expression was assessed by real-time PCR and immunohistochemistry. We estimated the association with platinum-free interval (PFI) and overall survival (OS) by Cox proportional hazards models. Median follow-up was 60 months.

Results

High GAPDH mRNA levels (HR 2.1, 95% CI 1.0-4.5) and low BEC-index (HR 0.47, 95% CI 0.23-0.95) were both independently associated with shorter PFI. Median PFI for patients with high GAPDH mRNA was 5.0 months compared to 10.1 months for low expression cases (p = 0.031). Similarly, median PFI for patients with low BEC-index based on mRNA was 5.3 months compared to 9.8 months for high BEC-index cases (p = 0.028).

Conclusions

High GAPDH or low BEC-index mRNA expression indicate early disease progression in advanced serous ovarian cancer.

Functional classification of cellular proteome profiles support the identification of drug resistance signatures in melanoma cells

Drug resistance is a major obstacle in melanoma treatment. Recognition of specific resistance patterns, the understanding of the patho-physiology of drug resistance, and identification of remaining options for individual melanoma treatment would greatly improve therapeutic success. We performed mass spectrometry-based proteome profiling of A375 melanoma cells and HeLa cells characterized as sensitive to cisplatin in comparison to cisplatin resistant M24met and TMFI melanoma cells. Cells were fractionated into cytoplasm, nuclei and secretome and the proteome profiles classified according to Gene Ontology. The cisplatin resistant cells displayed increased expression of lysosomal as well as Ca²⁺ ion binding and cell adherence proteins. These findings were confirmed using Lysotracker Red staining and cell adhesion assays with a panel of extracellular matrix proteins. To discriminate specific survival proteins, we selected constitutively expressed proteins of resistant M24met cells which were found expressed upon challenging the sensitive A375 cells. Using the CPL/MUW proteome database, the selected lysosomal, cell adherence and survival proteins apparently specifying resistant cells were narrowed down to 47 proteins representing a potential resistance signature. These were tested against our proteomics database comprising more than 200 different cell types/cell states for its predictive power. We provide evidence that this signature enables the automated assignment of resistance features as readout from proteome profiles of any human cell type. Proteome profiling and bioinformatic processing may thus support the understanding of drug resistance mechanism, eventually guiding patient tailored therapy.

Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

Targeting cellular metabolism to improve cancer therapeutics

The metabolic properties of cancer cells diverge significantly from those of normal cells. Energy production in cancer cells is abnormally dependent on aerobic glycolysis. In addition to the dependency on glycolysis, cancer cells have other atypical metabolic characteristics such as increased fatty acid synthesis and increased rates of glutamine metabolism. Emerging evidence shows that many features characteristic to cancer cells, such as dysregulated Warburg-like glucose metabolism, fatty acid synthesis and glutaminolysis are linked to therapeutic resistance in cancer treatment. Therefore, targeting cellular metabolism may improve the response to cancer therapeutics and the combination of chemotherapeutic drugs with cellular metabolism inhibitors may represent a promising strategy to overcome drug resistance in cancer therapy. Recently, several review articles have summarized the anticancer targets in the metabolic pathways and metabolic inhibitor-induced cell death pathways, however, the dysregulated metabolism in therapeutic resistance, which is a highly clinical relevant area in cancer metabolism research, has not been specifically addressed. From this unique angle, this review article will discuss the relationship between dysregulated cellular metabolism and cancer drug resistance and how targeting of metabolic enzymes, such as glucose transporters, hexokinase, pyruvate kinase M2, lactate dehydrogenase A, pyruvate dehydrogenase kinase, fatty acid synthase and glutaminase can enhance the efficacy of common therapeutic agents or overcome resistance to chemotherapy or radiotherapy.

Proteomic analysis identified DJ-1 as a cisplatin resistant marker in non-small cell lung cancer

The aim of study is to identify cisplatin-resistance associated biomarkers for non-small cell lung cancers (NSCLC). We use two-dimensional electrophoresis (2-DE) combined with MALDI-TOF mass spectrometry to compare the proteome between lung cancer cell line A549 and its cisplatin-resistant subline A549/DDP. Nine cisplatin resistance-related proteins were identified, and DJ-1, one of the differently expressed proteins, was selected for further validation and evaluation. Immunohistochemical results demonstrated that high expression level of DJ-1 was associated with cisplatin resistance and a predictor for poor prognosis in 67 locally advanced NSCLC patients. Furthermore, in vitro results showed that silencing DJ-1 increased the proliferation inhibitory effect of cisplatin to A549/DDP cells. In conclusion, DJ-1 might play an important role in the resistibility to cisplatin, and it could also act as a novel candidate biomarker for predicting the response of NSCLC patients to cisplatin-based chemotherapy.

[Enhanced cisplatin cytotoxicity by RNA interfering the excision repair cross-complementing gene 1 in lung cancer cell A549/DDP]

BACKGROUND AND OBJECTIVE

The excision repair cross-complementing gene 1 (ERCC1), which is important in the repair of cisplatin-DNA adducts, was reported to be related to cisplatin resistance in tumor cells. The aim of this study is to investigate the changes of cisplatin sensitivity by silencing ERCC1 gene in lung cancer cell.

METHODS

The small interfering RNA (siRNA) targeting ERCC1 gene was designed and synthesized, and transfected to lung cancer cell A549/DDP. The mRNA and protein expression levels of ERCC1 were evaluated by RT-PCR and Western blot. The changes of cisplatin sensitivity after RNA interference were examined by methyl thiazolyl assay.

RESULTS

In A549/DDP cell, the mRNA and protein levels of ERCC1 were decreased and the sensitivity to cisplatin was increased from 12.49 μg/mL to 9.27 μg/mL after transfection.

CONCLUSIONS

The sensitivity to cisplatin of lung cancer cell A549/DDP could be enhanced by RNA interfering ERCC1 gene targeted code 346.