Integrated Analysis of Gene Expression Profiles Associated with Response of Platinum/Paclitaxel-Based Treatment in Epithelial Ovarian Cancer

Purpose

This study aims to explore gene expression signatures and serum biomarkers to predict intrinsic chemoresistance in epithelial ovarian cancer (EOC).

Patients and Methods

Gene expression profiling data of 322 high-grade EOC cases between 2009 and 2010 in The Cancer Genome Atlas project (TCGA) were used to develop and validate gene expression signatures that could discriminate different responses to first-line platinum/paclitaxel-based treatments. A gene regulation network was then built to further identify hub genes responsible for differential gene expression between the complete response (CR) group and the progressive disease (PD) group. Further, to find more robust serum biomarkers for clinical application, we integrated our gene signatures and gene signatures reported previously to identify secretory protein-encoding genes by searching the DAVID database. In the end, gene-drug interaction network was constructed by searching Comparative Toxicogenomics Database (CTD) and literature.

Results

A 349-gene predictive model and an 18-gene model independent of key clinical features with high accuracy were developed for prediction of chemoresistance in EOC. Among them, ten important hub genes and six critical signaling pathways were identified to have important implications in chemotherapeutic response. Further, ten potential serum biomarkers were identified for predicting chemoresistance in EOC. Finally, we suggested some drugs for individualized treatment.

Conclusion

We have developed the predictive models and serum biomarkers for platinum/paclitaxel response and established the new approach to discover potential serum biomarkers from gene expression profiles. The potential drugs that target hub genes are also suggested.     

A strategy to reveal potential glycan markers from serum glycoproteins associated with breast cancer progression

Aberrant glycosylation on glycoproteins that are either presented on the surface or secreted by cancer cells is a potential source of disease biomarkers and provides insights into disease pathogenesis. N-Glycans of the total serum glycoproteins from advanced breast cancer patients and healthy individuals were sequenced by HPLC with fluorescence detection coupled with exoglycosidase digestions and mass spectrometry. We observed a significant increase in a trisialylated triantennary glycan containing alpha1,3-linked fucose which forms part of the sialyl Lewis x epitope. Following digestion of the total glycan pool with a combination of sialidase and beta-galactosidase, we segregated and quantified a digestion product, a monogalactosylated triantennary structure containing alpha1,3-linked fucose. We compared breast cancer patients and controls and detected a 2-fold increase in this glycan marker in patients. In 10 patients monitored longitudinally, we showed a positive correlation between this glycan marker and disease progression and also demonstrated its potential as a better indicator of metastasis compared to the currently used biomarkers, CA 15-3 and carcinoembryonic antigen (CEA). A pilot glycoproteomic study of advanced breast cancer serum highlighted acute-phase proteins alpha1-acid glycoprotein, alpha1-antichymotrypsin, and haptoglobin beta-chain as contributors to the increase in the glycan marker which, when quantified from each of these proteins, marked the onset of metastasis in advance of the CA 15-3 marker. These preliminary findings suggest that specific glycans and glycoforms of proteins may be candidates for improved markers in the monitoring of breast cancer progression.     

Circulating miR-19a and miR-205 in Serum May Predict the Sensitivity of Luminal A Subtype of Breast Cancer Patients to Neoadjuvant Chemotherapy with Epirubicin Plus Paclitaxel

Background

The luminal A subtype of breast cancer has a good prognosis and is sensitive to endocrine therapy but is less sensitive to chemotherapy. It is necessary to identify biomarkers to predict chemosensitivity and avoid over-treatment. We hypothesized that miRNAs in the serum might be associated with chemosensitivity.

Methods

Sixty-eight breast cancer patients received neoadjuvant chemotherapy with epirubicin plus paclitaxel. The serum of the patients was collected before chemotherapy and stored at −80°C. The samples were classified into two groups in term of the chemosensitivity. We identified the differential expression patterns of miRNAs between the chemotherapy sensitive and resistant groups using microRNA profiling. Four miRNAs that were differentially expressed between the two groups were further validated in another 56 samples. We created a model fitting formula and a receiver operating characteristics (ROC) curve using logistic regression analysis to evaluate the prediction potency.

Results

We identified 8 miRNAs differentially expressed between the two groups: 6 miRNAs were up-regulated, and 2 miRNAs were down-regulated in the resistant group compared with the sensitive group. The expression of miR-19a and miR-205 were determined to have significant differences between the two groups (P<0.05). A predictive model of these two miRNAs was created by the logistic regression analysis. The probability of this model was 89.71%. Based on the ROC curve, the specificity was 75.00%, and the sensitivity was 81.25%.

Conclusions

The combination of miR-19a and miR-205 in the serum may predict the chemosensitivity of luminal A subtype of breast cancer to epirubicin plus paclitaxel neoadjuvant chemotherapy.     

Proteomic identification of predictive biomarkers of resistance to neoadjuvant chemotherapy in luminal breast cancer: a possible role for 14-3-3 theta/tau and tBID?

Introduction

Chemotherapy resistance is a major obstacle in effective neoadjuvant treatment for estrogen receptor-positive breast cancer. The ability to predict tumour response would allow chemotherapy administration to be directed towards only those patients who would benefit, thus maximising treatment efficiency. We aimed to identify putative protein biomarkers associated with chemotherapy resistance, using fresh tumour samples with antibody microarray analysis and then to perform pilot clinical validation experiments.

Materials and methods

Chemotherapy resistant and chemotherapy sensitive tumour samples were collected from breast cancer patients who had received anthracycline based neoadjuvant therapy consisting of epirubicin with cyclophosphamide followed by docetaxel. A total of 5 comparative proteomics experiments were performed using invasive ductal carcinomas which demonstrated estrogen receptor positivity (luminal subtype). Protein expression was compared between chemotherapy resistant and chemotherapy sensitive tumour samples using the Panorama XPRESS Profiler725 antibody microarray containing 725 antibodies from a wide variety of cell signalling and apoptosis pathways. A pilot series of archival samples was used for clinical validation of putative predictive biomarkers.

Results

AbMA analysis revealed 38 differentially expressed proteins which demonstrated at least 1.8 fold difference in expression in chemotherapy resistant tumours and 7 of these proteins (Zyxin, 14-3-3 theta/tau, tBID, Pinin, Bcl-xL, RIP and MyD88) were found in at least 2 experiments. Clinical validation in a pilot series of archival samples revealed 14-3-3 theta/tau and tBID to be significantly associated with chemotherapy resistance.

Conclusions

For the first time, antibody microarrays have been used to identify proteins associated with chemotherapy resistance using fresh breast cancer tissue. We propose a potential role for 14-3-3 theta/tau and tBID as predictive biomarkers of neoadjuvant chemotherapy resistance in breast cancer. Further validation in a larger sample series is now required.     

Phosphosignature Predicts Dasatinib Response in Non-small Cell Lung Cancer

Targeted drugs are less toxic than traditional chemotherapeutic therapies; however, the proportion of patients that benefit from these drugs is often smaller. A marker that confidently predicts patient response to a specific therapy would allow an individual therapy selection most likely to benefit the patient. Here, we used quantitative mass spectrometry to globally profile the basal phosphoproteome of a panel of non-small cell lung cancer cell lines. The effect of the kinase inhibitor dasatinib on cellular growth was tested against the same panel. From the phosphoproteome profiles, we identified 58 phosphorylation sites, which consistently differ between sensitive and resistant cell lines. Many of the corresponding proteins are involved in cell adhesion and cytoskeleton organization. We showed that a signature of only 12 phosphorylation sites is sufficient to accurately predict dasatinib sensitivity. Four of the phosphorylation sites belong to integrin β4, a protein that mediates cell-matrix or cell-cell adhesion. The signature was validated in cross-validation and label switch experiments and in six independently profiled breast cancer cell lines. The study supports that the phosphorylation of integrin β4, as well as eight further proteins comprising the signature, are candidate biomarkers for predicting response to dasatinib in solid tumors. Furthermore, our results show that identifying predictive phosphorylation signatures from global, quantitative phosphoproteomic data is possible and can open a new path to discovering molecular markers for response prediction.     

Biomarkers discovery in cancer--up-dates in methodology

Biomarkers are biomolecules that can indicate normal/pathological processes, or physiological responses to therapy. Due to the serum abundance in proteins, such as albumin and lypo/glycoproteins, biomarkers are difficult to assess. Serum biomarkers identification can contribute to personalized medicine and improve cancer diagnostic and prognostic. The paper summarizes some of the proteomics techniques and the workflow used for protein signatures identification associated to cancer development. Thus, biomarkers validated for prostatic, breast, cervical or lung cancers are presented as examples for clinical application of serum markers. In spite of the continuous research efforts, there are only few validated biomarkers that have proved a good predictive power in cancer. Modern technology and the combination of various techniques used for proteins quantification represent important means for the identification and validation of new biomarkers.     

Modulation of Mutational Landscape in HER2-Positive Breast Cancer after Neoadjuvant Chemotherapy

IntroductionIn early-stage HER2 positive breast cancer (BC) patients, tumor response to neoadjuvant chemotherapy (NACT) predict survival outcomes. Patients achieving less than pathological complete response (pCR) have a worse prognosis, however, this group is heterogeneous. Nowadays limited data on predictive/prognostic biomarkers in patients with residual cancer disease are available.MethodsUsing next-generation sequencing technology, we evaluated a panel of 21 cancer genes in a group of HER2 positive BC patients with residual disease after NACT. A control group of patients who achieved the pCR was selected too. The BC mutational profile was analyzed on both the tumor diagnostic biopsy and matched residual disease.ResultsOverall, the detection rate of mutations was 79% in the No-pCR group versus 90% in the pCR cohort and 98% in the residual BC. The most mutated genes were TP53 and PIK3CA. No correlations between single gene mutations and survival outcomes were found. In no-pCR cohort, 52% of patients had different mutational profile after NACT, 69% of them had an increased in the number of mutated genes. Mutational profile changes from diagnostic biopsy to residual BC were a negative prognostic factor in term of relapse free survival: recurrence probability in different gene profile sub-group was 42% vs 0% in the same profile one (P = .019).ConclusionsTreatment selective pressure on tumor cells due to NACT changed the gene mutational profile in more than half of BC patient with residual tumor disease. Treatment-induced gene mutations significantly increase the risk of relapse. Profiling primary and residual BC is a major step in order to further personalized adjuvant treatment strategy.     

Potentiated DNA Damage Response in Circulating Breast Tumor Cells Confers Resistance to Chemotherapy

Circulating tumor cells (CTCs) are seeds for cancer metastasis and are predictive of poor prognosis in breast cancer patients. Whether CTCs and primary tumor cells (PTCs) respond to chemotherapy differently is not known. Here, we show that CTCs of breast cancer are more resistant to chemotherapy than PTCs because of potentiated DNA repair. Surprisingly, the chemoresistance of CTCs was recapitulated in PTCs when they were detached from the extracellular matrix. Detachment of PTCs increased the levels of reactive oxygen species and partially activated the DNA damage checkpoint, converting PTCs to a CTC-like state. Inhibition of checkpoint kinases Chk1 and Chk2 in CTCs reduces the basal checkpoint response and sensitizes CTCs to DNA damage in vitro and in mouse xenografts. Our results suggest that DNA damage checkpoint inhibitors may benefit the chemotherapy of breast cancer patients by suppressing the chemoresistance of CTCs and reducing the risk of cancer metastasis.     

Elevation in Inflammatory Serum Biomarkers Predicts Response to Trastuzumab-Containing Therapy

Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP) in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml) or CRP (>7.25 mg/l) was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.     

Identification of platinum-resistance associated proteins through proteomic analysis of human ovarian cancer cells and their platinum-resistant sublines

Chemoresistance is a major therapeutic obstacle in cancer patients, and the mechanisms of drug resistance are not fully understood. In the present study, we established platinum-resistant human ovarian cancer cell lines and identified differentially expressed proteins related to platinum resistance. The total proteins of two sensitive (SKOV3 and A2780) and four resistant (SKOV3/CDDP, SKOV3/CBP, A2780/CDDP, and A2780/CBP) human ovarian cancer cell lines were isolated by two-dimensional gel electrophoresis (2-DE). The differentially expressed proteins were identified using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS). In total, 57 differential protein spots were identified, and five proteins, including annexin A3, destrin, cofilin 1, Glutathione-S-transferase omega 1 (GSTO1-1), and cytosolic NADP+-dependent isocitrate dehydrogenase (IDHc), were found to be co-instantaneous significance compared with their parental cells. The expression of the five proteins was validated by quantitative PCR and western blot, and the western blot results showed complete consistency with proteomic techniques. The five proteins are hopeful to become candidates for platinum resistance. These may be useful for further study of resistance mechanisms and screening of resistant biomarkers.     

Identification of Multiple Novel Protein Biomarkers Shed by Human Serous Ovarian Tumors into the Blood of Immunocompromised Mice and Verified in Patient Sera

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples.     

Proteomics for identifying mechanisms and biomarkers of drug resistance in cancer

A major problem in chemotherapy of cancer patients is drug resistance as well as unpredictable response to treatment. During chemotherapy, multiple alterations of genetics and epigenetics that contribute to chemoresistance take place, eventually impacting on disease outcome. A more complex picture of the mechanisms of drug resistance is now emerging through application of high-throughput proteomics technology. We have entered an exciting time where proteomics are being applied to characterize the mechanisms of drug resistance, and to identify biomarkers for predicting response to chemotherapy, thereby leading to personalized therapeutic strategies of cancer patients. Comparative proteomics have identified a large number of differentially expressed proteins associated with chemoresistance. Although roles and mechanisms of such proteins in chemoresistance need to be further proved, at least some of them may be potential biomarkers for predicting chemotherapeutic response. Herein, we review the recent advancements on proteomic investigation of chemoresistance in human cancer, and emphasize putative biomarkers for predicting chemotherapeutic response and possible mechanisms of chemoresistance identified through proteomic approaches. Suggested avenues for future work are discussed.     

Doxorubicin induces cell death in breast cancer cells regardless of Survivin and XIAP expression levels

Breast cancer is the leading cause of deaths in women around the world. Resistance to therapy is the main cause of treatment failure and still little is known about predictive biomarkers for response to systemic therapy. Increasing evidence show that Survivin and XIAP overexpression is closely associated with chemoresistance and poor prognosis in breast cancer. However, their impact on resistance to doxorubicin (dox), a chemotherapeutic agent widely used to treat breast cancer, is poorly understood. Here, we demonstrated that dox inhibited cell viability and induced DNA fragmentation and activation of caspases-3, -7 and -9 in the breast cancer-derived cell lines MCF7 and MDA-MB-231, regardless of different p53 status. Dox exposure resulted in reduction of Survivin and XIAP mRNA and protein levels. However, when we transfected cells with a Survivin-encoding plasmid, we did not observe a cell death-resistant phenotype. XIAP and Survivin silencing, either alone or in combination, had no effect on breast cancer cells sensitivity towards dox. Altogether, we demonstrated that breast cancer cells are sensitive to the chemotherapeutic agent dox irrespective of Survivin and XIAP expression levels. Also, our findings suggest that dox-mediated modulation of Survivin and XIAP might sensitize cells to taxanes when used in a sequential regimen.     

PD-L1 versus tumor mutation burden: Which is the better immunotherapy biomarker in advanced non-small cell lung cancer?

PD-L1 and tumor mutation burden (TMB) are the most widely used immunotherapy biomarkers to identify populations who would attain clinical benefit, with the higher values predicting better therapeutic efficacy. This review addresses the predictive values and unresolved challenges of these two biomarkers. PD-1 and PD-L1 inhibitors have induced durable and effective responses in patients with advanced non-small cell lung cancer, confirmed by multiple clinical trials and real-world studies. Different clinical trials, involving both PD-1/PD-L1 inhibitors alone and combination regimens, adopted either PD-L1 or TMB to stratify the patients, although the predictive capabilities of these two biomarkers are different. In the first-line setting, PD-L1 of 50% or more as a cut-off value can help select candidates for pembrolizumab or atezolizumab monotherapy; however, these two biomarkers poorly predict the efficacy of immunotherapy combination regimens as first-line treatments. In the second-line setting, although patients can benefit from nivolumab regardless of PD-L1 expression, both PD-L1 and blood TMB can be used as biomarkers to find patients suitable for atezolizumab. Except for inaccurate predictiveness, there are many unresolved problems with regard to the two biomarkers, such as the lack of standard detection methods, and their susceptibilities to other dynamic changes. The predictive values of TMB and PD-L1 were low in most circumstances; however, PD-L1 expression greater than ≥ 50% can help select appropriate patients for pembrolizumab and atezolizumab, respectively, as first-line monotherapies. Higher PD-L1 or TMB was associated with greater efficacy for atezolizumab as a second-line monotherapy.     

Serum exosomal lncRNA XIST is a potential non-invasive biomarker to diagnose recurrence of triple-negative breast cancer

Exosomal lncRNAs secreted by cancer cells can serve as potential biomarkers in the diagnosis and prognosis of various tumours. Here, we are committed to explore the diagnostic and prognostic value of serum exosomal XIST secreted by tumour cells to predict recurrence in patients with triple-negative breast cancer (TNBC). Significant increments in XIST and exo-XIST from tumour tissues and blood serum were found in reoccurring TNBC patients by comparison with non-recurrences. Levels of serum exo-XIST were only significantly increased in TNBC recurrence and no association with other clinicopathological parameters. Additionally, serum exo-XIST levels could be served as an assessment of change in the load of triple-negative breast cancer. Expressions of exo-XIST were markedly decreased after resection of the primary breast tumours and obviously elevated at the time of recurrence. Finally, an obvious association was identified between serum exo-XIST levels and a poorer overall survival (OS) in TNBC patients. Levels of serum exo-XIST may serve as a diagnostic and prognostic biomarker to predict the recurrent TNBC-loading status.     

Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment

Impaired DNA damage response pathways may create vulnerabilities of cancer cells that can be exploited therapeutically. One such selective vulnerability is the sensitivity of BRCA1- or BRCA2-defective tumors (hence defective in DNA repair by homologous recombination, HR) to inhibitors of the poly(ADP-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i combinations with camptothecin or ionizing radiation. Furthermore, monitoring PARsylation and Rad51 foci formation as surrogate markers for PARP activity and HR, respectively, supported their candidacy for biomarkers of PARP-1i responses. As to resistance mechanisms, we confirmed the role of the multidrug resistance efflux transporters and its reversibility. More importantly, we demonstrated that shRNA lentivirus-mediated depletion of 53BP1 in human BRCA1-mutant breast cancer cells increased their resistance to PARP-1i. Given the preferential loss of 53BP1 in BRCA-defective and triple-negative breast carcinomas, our findings warrant assessment of 53BP1 among candidate predictive biomarkers of response to PARPi. Overall, this study helps characterize genetic and functional determinants of cellular responses to PARP-1i and contributes to the search for biomarkers to exploit PARP inhibitors in cancer therapy.     

Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment

Impaired DNA damage response pathways may create vulnerabilities of cancer cells that can be exploited therapeutically. One such selective vulnerability is the sensitivity of BRCA1- or BRCA2-defective tumors (hence defective in DNA repair by homologous recombination, HR) to inhibitors of the poly(ADP-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i combinations with camptothecin or ionizing radiation. Furthermore, monitoring PARsylation and Rad51 foci formation as surrogate markers for PARP activity and HR, respectively, supported their candidacy for biomarkers of PARP-1i responses. As to resistance mechanisms, we confirmed the role of the multidrug resistance efflux transporters and its reversibility. More importantly, we demonstrated that shRNA lentivirus-mediated depletion of 53BP1 in human BRCA1-mutant breast cancer cells increased their resistance to PARP-1i. Given the preferential loss of 53BP1 in BRCA-defective and triple-negative breast carcinomas, our findings warrant assessment of 53BP1 among candidate predictive biomarkers of response to PARPi. Overall, this study helps characterize genetic and functional determinants of cellular responses to PARP-1i and contributes to the search for biomarkers to exploit PARP inhibitors in cancer therapy.