Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative breast cancer (TNBC) and human epidermal growth factor receptor 2 positive breast cancer, are confronted with a heightened risk of drug resistance, often leading to early recurrence; the biomarkers and biological processes associated with recurrence is still unclear. In this study, we analyzed bulk RNA sequencing (RNA-seq) data from 285 cancer and paracancerous samples from 155 TNBC patients, along with transcriptome data from 11 independent public cohorts comprising 7,449 breast cancer patients and 26 single-cell RNA-seq datasets. Our results revealed differential enrichment of nerve-related pathways between TNBC patients with and without 10-year recurrence-free survival. We developed an early recurrence index (ERI) using a machine learning model and constructed a nomogram that accurately predicts the 10-year survival of ERneg patients (area under the curve [AUC]Training = 0.79; AUCTest = 0.796). Further analysis linked ERI to enhanced neural function and immunosuppression. Additionally, we identified EN1, the most significant ERI gene, as a potential biomarker that may regulate the tumor microenvironment and sensitize patients to immunotherapy.

Transcriptome-wide analysis reveals potential roles of CFD and ANGPTL4 in fibroblasts regulating B cell lineage for extracellular matrix-driven clustering and novel avenues for immunotherapy in breast cancer

BACKGROUND

The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive.

METHODS

Transcriptome and genome data of breast cancer patients from TCGA database was downloaded. Patients were classified into different clusters by using non-negative matrix factorization (NMF) based on signatures of ECM components and regulators. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify core genes related to ECM clusters. Additional 10 independent public cohorts including Metabric, SCAN_B, GSE12276, GSE16446, GSE19615, GSE20685, GSE21653, GSE58644, GSE58812, and GSE88770 were collected to construct Training or Testing cohort, following machine learning calculating ECM correlated index (ECI) for survival analysis. Pathway enrichment and correlation analysis were used to explore the relationship among ECM clusters, ECI and TME. Single-cell transcriptome data from GSE161529 was processed for uncovering the differences among ECM clusters.

RESULTS

Using NMF, we identified three ECM clusters in the TCGA database: C1 (Neuron), C2 (ECM), and C3 (Immune). Subsequently, WGCNA was employed to pinpoint cluster-specific genes and develop a prognostic model. This model demonstrated robust predictive power for breast cancer patient survival in both the Training cohort (n = 5,392, AUC = 0.861) and the Testing cohort (n = 1,344, AUC = 0.711). Upon analyzing the tumor microenvironment (TME), we discovered that fibroblasts and B cell lineage were the core cell types associated with the ECM cluster phenotypes. Single-cell RNA sequencing data further revealed that angiopoietin like 4 (ANGPTL4)+ fibroblasts were specifically linked to the C2 phenotype, while complement factor D (CFD)+ fibroblasts characterized the other ECM clusters. CellChat analysis indicated that ANGPTL4+ and CFD+ fibroblasts regulate B cell lineage via distinct signaling pathways. Additionally, analysis using the Kaplan-Meier Plotter website showed that CFD was favorable for immunotherapy response, whereas ANGPTL4 negatively impacted the outcomes of cancer patients receiving immunotherapy.

CONCLUSION

We identified distinct ECM clusters in breast cancer patients, irrespective of molecular subtypes. Additionally, we constructed an effective prognostic model based on these ECM clusters and recognized ANGPTL4+ and CFD+ fibroblasts as potential biomarkers for immunotherapy in breast cancer.

GPBP or CERT: The Roles in Autoimmunity, Cancer or Neurodegenerative Disease-A Systematic Review

In 1999, Goodpasture antigen-binding protein (GPBP) was identified as a protein interacting with the N-terminal region of the human Goodpasture antigen, linked to collagen IV in patients with Goodpasture syndrome, an autoimmune disease. In 2003, a splice variant lacking a serine-rich domain was discovered, which is involved in the cytosolic transport of ceramide, leading to its renaming as Ceramide Transfer Protein (CERT). This dual functionality has sparked debate regarding the roles of GPBP/CERT, as they appear to participate in distinct research fields and are implicated in various pathologies. This review follows the guidelines of the Preferred Reporting Items for Systematic Reviews (PRISMA). It compiles data from searches on Medline (PubMed) and Web of Science conducted between February and November 2022. Out of 465 records, 47 publications were selected for review. The literature predominantly focuses on GPBP/CERT as ceramide transporters. Notably, no studies contradict either hypothesis, with substantial scientific evidence supporting both roles. The need for further research is clear, and new insights into these proteins' involvement in multiple pathologies could drive future therapeutic strategies. GPBP and CERT are multifunctional proteins with roles beyond collagen organization and ceramide transport, extending to autoimmune disorders, neurodegenerative diseases, and cancer. The ongoing controversy highlights the necessity for continued investigation, which promises to offer significant insights and potential therapeutic avenues.

Peroxiporins in Triple-Negative Breast Cancer: Biomarker Potential and Therapeutic Perspectives

Triple-negative breast cancer (TNBC) remains one of the most challenging subtypes since it is initially characterized by the absence of specific biomarkers and corresponding targeted therapies. Advances in methodology, translational informatics, genomics, and proteomics have significantly contributed to the identification of therapeutic targets. The development of innovative treatments, such as antibody-drug conjugates and immune checkpoint inhibitors, alongside chemotherapy, has now become the standard of care. However, the quest for biomarkers defining therapy outcomes is still ongoing. Peroxiporins, which comprise a subgroup of aquaporins, which are membrane pores facilitating the transport of water, glycerol, and hydrogen peroxide, have emerged as potential biomarkers for therapy response. Research on peroxiporins reveals their involvement beyond traditional channeling activities, which is also reflected in their cellular localization and roles in cellular signaling pathways. This research on peroxiporins provides fresh insights into the mechanisms of therapy resistance in tumors, offering potential avenues for predicting treatment outcomes and tailoring successful TNBC therapies.

Basal-epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by extensive intratumoral heterogeneity, high metastasis, and chemoresistance, leading to poor clinical outcomes. Despite progress, the mechanistic basis of these aggressive behaviors remains poorly understood. Using single-cell and spatial transcriptome analysis, here we discovered basal epithelial subpopulations located within the stroma that exhibit chemoresistance characteristics. The subpopulations are defined by distinct signature genes that show a frequent gain in copy number and exhibit an activated epithelial-to-mesenchymal transition program. A subset of these genes can accurately predict chemotherapy response and are associated with poor prognosis. Interestingly, among these genes, elevated ITGB1 participates in enhancing intercellular signaling while ACTN1 confers a survival advantage to foster chemoresistance. Furthermore, by subjecting the transcriptional signatures to drug repurposing analysis, we find that chemoresistant tumors may benefit from distinct inhibitors in treatment-naive versus post-NAC patients. These findings shed light on the mechanistic basis of chemoresistance while providing the best-in-class biomarker to predict chemotherapy response and alternate therapeutic avenues for improved management of TNBC patients resistant to chemotherapy.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

Combining causal and correlative approaches to discover biomarkers of response to paclitaxel

We recently discovered a putative paclitaxel response predictive biomarker for glioblastoma and breast cancer using the whole genome CRISPR knockout screen. The biomarker candidate was validated in two independent breast cancer patient cohorts that received taxane treatment. To further evaluate the potential application of this biomarker in the clinic for patients with glioblastoma, a prospective validation in cohorts of patients with glioblastoma is essential and will be performed as part of our ongoing phase II clinical trial (NCT04528680). The validation of novel biomarkers of susceptibility to therapy is critical to elucidate the efficacy signal of therapeutic agents. This is especially important in the context of glioblastoma, where therapeutic benefit is variable and unpredictable, leading to negative trials, yet the outcome of subset of patients has outperformed expectations.

Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer

BACKGROUND

While the efficacy of neoadjuvant chemotherapy (NACT) in treating triple-negative breast cancer (TNBC) is generally accepted, not all patients derive benefit from this preoperative treatment. Presently, there are no validated biomarkers to predict the NACT response, and previous attempts to develop predictive classifiers based on gene expression data have not demonstrated clinical utility. However, predictive models incorporating biological constraints have shown increased robustness and improved performance compared to agnostic classifiers.

METHODS

We used the preoperative transcriptomic profiles from 298 patients with TNBC to train and test a rank-based classifier, k-top scoring pairs, to predict whether the patient will have pathological complete response (pCR) or residual disease (RD) following NACT. To reduce overfitting and enhance the signature's interpretability, we constrained the training process to genes involved in the Notch signaling pathway. Subsequently, we evaluated the signature performance on two independent cohorts with 75 and 71 patients. Finally, we assessed the prognostic value of the signature by examining its association with relapse-free survival (RFS) using Kaplan‒Meier (KM) survival estimates and a multivariate Cox proportional hazards model.

RESULTS

The final signature consists of five gene pairs, whose relative ordering can be predictive of the NACT response. The signature has a robust performance at predicting pCR in TNBC patients with an area under the ROC curve (AUC) of 0.76 and 0.85 in the first and second testing cohorts, respectively, outperforming other gene signatures developed for the same purpose. Additionally, the signature was significantly associated with RFS in an independent TNBC patient cohort even after adjusting for T stage, patient age at the time of diagnosis, type of breast surgery, and menopausal status.

CONCLUSION

We introduce a robust gene signature to predict pathological complete response (pCR) in patients with TNBC. This signature applies easily interpretable, rank-based decision rules to genes regulated by the Notch signaling pathway, a known determinant in breast cancer chemoresistance. The robust predictive and prognostic performance of the signature make it a strong candidate for clinical implementation, aiding in the stratification of TNBC patients undergoing NACT.

Molecular Biology Mechanisms and Emerging Therapeutics of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that is conventionally characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2), accounting for approximately 15-20% of all breast cancers. Compared to other molecular phenotypes, TNBC is typically associated with high malignancy and poor prognosis. Cytotoxic agents have been the mainstay of treatment for the past few decades due to the lack of definitive targets and limited therapeutic interventions. However, recent developments have demonstrated that TNBC has peculiar molecular classifications and biomarkers, which provide the possibility of evolving treatment from basic cytotoxic chemotherapy to an expanding domain of targeted therapies. This review presents a framework for understanding the current clinical experience surrounding molecular biology mechanisms in TNBC (Figure 1). Including immunotherapy, polymerase (PARP) and PI3K/AKT pathway inhibitors, antibody-drug conjugates, and androgen receptor (AR) blockade. Additionally, the role of miRNA therapeutics targeting TNBC and potential strategies targeting cancer stem cells (CSCs) are discussed and highlighted. As more and more treatments arise on the horizon, we believe that patients with TNBC will have a new sense of hope.

Myeloid Cell Leukemia 1 Small Molecule Inhibitor S63845 Synergizes with Cisplatin in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive cancer that lacks specific molecular targets that are often used for therapy. The refractory rate of TNBC to broad-spectrum chemotherapy remains high; however, the combination of newly developed treatments with the current standard of care has delivered promising anti-tumor effects. One mechanism employed by TNBC to avoid cell death is the increased expression of the anti-apoptotic protein, myeloid cell leukemia 1 (MCL1). Multiple studies have demonstrated that increased MCL1 expression enables resistance to platinum-based chemotherapy. In addition to suppressing apoptosis, we recently demonstrated that MCL1 also binds and negatively regulates the transcriptional activity of TP73. TP73 upregulation is a critical driver of cisplatin-induced DNA damage response, and ultimately, cell death. We therefore sought to determine if the coadministration of an MCL1-targeted inhibitor with cisplatin could produce a synergistic response in TNBC. This study demonstrates that the MCL1 inhibitor, S63845, combined with cisplatin synergizes by inducing apoptosis while also decreasing proliferation in a subset of TNBC cell lines. The use of combined MCL1 inhibitors with cisplatin in TNBC effectively initiates TAp73 anti-tumor effects on cell cycle arrest and apoptosis. This observation provides a molecular profile that can be exploited to identify sensitive TNBCs.

Fluorouracil exacerbates alpha-crystallin B chain-mediated cell migration in triple-negative breast cancer cell lines

Among triple-negative breast cancer (TNBC) subtypes, the basal-like 2 (BL2) subtype shows the lowest survival rate and the highest risk of metastasis after treatment with chemotherapy. Research has shown that αB-crystallin (CRYAB) is more highly expressed in the basal-like subtypes than in the other subtypes and is associated with brain metastasis in TNBC patients. We therefore hypothesized that αB-crystallin is associated with increased cell motility in the BL2 subtype after treatment with chemotherapy. Here, we evaluated the effect of fluorouracil (5-FU), a typical chemotherapy for the treatment of TNBC, on cell motility by utilizing a cell line with high αB-crystallin expression (HCC1806). A wound healing assay revealed that 5-FU significantly increased cell motility in HCC1806 cells, but not in MDA-MB-231 cells, which have low αB-crystallin expression. Also, cell motility was not increased by 5-FU treatment in HCC1806 cells harboring stealth siRNA targeting CRYAB. In addition, the cell motility of MDA-MB-231 cells overexpressing αB-crystallin was significantly higher than that of MDA-MB-231 cells harboring a control vector. Thus, 5-FU increased cell motility in cell lines with high, but not low, αB-crystallin expression. These results suggest that 5-FU-induced cell migration is mediated by αB-crystallin in the BL2 subtype of TNBC.

The Critical Impact of Sphingolipid Metabolism in Breast Cancer Progression and Drug Response

Breast cancer is the second leading cause of cancer-related death in women in the world, and its management includes a combination of surgery, radiation therapy, chemotherapy, and immunotherapy, whose effectiveness depends largely, but not exclusively, on the molecular subtype (Luminal A, Luminal B, HER2+ and Triple Negative). All breast cancer subtypes are accompanied by peculiar and substantial changes in sphingolipid metabolism. Alterations in sphingolipid metabolite levels, such as ceramides, dihydroceramide, sphingosine, sphingosine-1-phosphate, and sphingomyelin, as well as in their biosynthetic and catabolic enzymatic pathways, have emerged as molecular mechanisms by which breast cancer cells grow, respond to or escape therapeutic interventions and could take on diagnostic and prognostic value. In this review, we summarize the current landscape around two main themes: 1. sphingolipid metabolites, enzymes and transport proteins that have been found dysregulated in human breast cancer cells and/or tissues; 2. sphingolipid-driven mechanisms that allow breast cancer cells to respond to or evade therapies. Having a complete picture of the impact of the sphingolipid metabolism in the development and progression of breast cancer may provide an effective means to improve and personalize treatments and reduce associated drug resistance.

Ablation of sphingosine kinase 2 suppresses fatty liver-associated hepatocellular carcinoma via downregulation of ceramide transfer protein

Hepatocellular carcinoma (HCC) accounts for 90% of primary liver cancer, the third leading cause of cancer-associated death worldwide. With the increasing prevalence of metabolic conditions, non-alcoholic fatty liver disease (NAFLD) is emerging as the fastest-growing HCC risk factor, and it imposes an additional layer of difficulty in HCC management. Dysregulated hepatic lipids are generally believed to constitute a deleterious environment cultivating the development of NAFLD-associated HCC. However, exactly which lipids or lipid regulators drive this process remains elusive. We report herein that sphingosine kinase 2 (SphK2), a key sphingolipid metabolic enzyme, plays a critical role in NAFLD-associated HCC. Ablation of Sphk2 suppressed HCC development in NAFLD livers via inhibition of hepatocyte proliferation both in vivo and in vitro. Mechanistically, SphK2 deficiency led to downregulation of ceramide transfer protein (CERT) that, in turn, decreased the ratio of pro-cancer sphingomyelin (SM) to anti-cancer ceramide. Overexpression of CERT restored hepatocyte proliferation, colony growth and cell cycle progression. In conclusion, the current study demonstrates that SphK2 is an essential lipid regulator in NAFLD-associated HCC, providing experimental evidence to support clinical trials of SphK2 inhibitors as systemic therapies against HCC.

Challenges for Triple Negative Breast Cancer Treatment: Defeating Heterogeneity and Cancer Stemness

The Triple Negative Breast Cancer (TNBC) subtype is known to have a more aggressive clinical course compared to other breast cancer subtypes. Targeted therapies for this type of breast cancer are limited and patients are mostly treated with conventional chemo- and radio-therapies which are not specific and do not target resistant cells. Therefore, one of the major clinical challenges is to find compounds that target the drug-resistant cell populations which are responsible for reforming secondary tumours. The molecular profiling of the different TNBC subtypes holds a promise for better defining these resistant cells specific to each tumour. To this end, a better understanding of TNBC heterogeneity and cancer stemness is required, and extensive genomic analysis can help to understand the disease complexity and distinguish new molecular drivers that can be targeted in the clinics. The use of persister cancer cell-targeting therapies combined with other therapies may provide a big advance to improve TNBC patients' survival.

Immunotherapy in triple-negative breast cancer: Insights into tumor immune landscape and therapeutic opportunities

Triple-negative breast cancer (TNBC) is a clinically aggressive subtype of breast cancer that represents 15-20% of breast tumors and is more prevalent in young pre-menopausal women. It is the subtype of breast cancers with the highest metastatic potential and recurrence at the first 5 years after diagnosis. In addition, mortality increases when a complete pathological response is not achieved. As TNBC cells lack estrogen, progesterone, and HER2 receptors, patients do not respond well to hormone and anti-HER2 therapies, and conventional chemotherapy remains the standard treatment. Despite efforts to develop targeted therapies, this disease continues to have a high unmet medical need, and there is an urgent demand for customized diagnosis and therapeutics. As immunotherapy is changing the paradigm of anticancer treatment, it arises as an alternative treatment for TNBC patients. TNBC is classified as an immunogenic subtype of breast cancer due to its high levels of tumor mutational burden and presence of immune cell infiltrates. This review addresses the implications of these characteristics for the diagnosis, treatment, and prognosis of the disease. Herein, the role of immune gene signatures and tumor-infiltrating lymphocytes as biomarkers in TNBC is reviewed, identifying their application in patient diagnosis and stratification, as well as predictors of efficacy. The expression of PD-L1 expression is already considered to be predictive of response to checkpoint inhibitor therapy, but the challenges regarding its value as biomarker are described. Moreover, the rationales for different formats of immunotherapy against TNBC currently under clinical research are discussed, and major clinical trials are highlighted. Immune checkpoint inhibitors have demonstrated clinical benefit, particularly in early-stage tumors and when administered in combination with chemotherapy, with several regimens approved by the regulatory authorities. The success of antibody-drug conjugates and research on other emerging approaches, such as vaccines and cell therapies, will also be addressed. These advances give hope on the development of personalized, more effective, and safe treatments, which will improve the survival and quality of life of patients with TNBC.

Gastric cancer biomarker analysis in patients treated with different adjuvant chemotherapy regimens within SAMIT, a phase III randomized controlled trial

Biomarkers for selecting gastric cancer (GC) patients likely to benefit from sequential paclitaxel treatment followed by fluorinated-pyrimidine-based adjuvant chemotherapy (sequential paclitaxel) were investigated using tissue samples of patients recruited into SAMIT, a phase III randomized controlled trial. Total RNA was extracted from 556 GC resection samples. The expression of 105 genes was quantified using real-time PCR. Genes predicting the benefit of sequential paclitaxel on overall survival, disease-free survival, and cumulative incidence of relapse were identified based on the ranking of p-values associated with the interaction between the biomarker and sequential paclitaxel or monotherapy groups. Low VSNL1 and CD44 expression predicted the benefit of sequential paclitaxel treatment for all three endpoints. Patients with combined low expression of both genes benefitted most from sequential paclitaxel therapy (hazard ratio = 0.48 [95% confidence interval, 0.30-0.78]; p < 0.01; interaction p-value < 0.01). This is the first study to identify VSNL1 and CD44 RNA expression levels as biomarkers for selecting GC patients that are likely to benefit from sequential paclitaxel treatment followed by fluorinated-pyrimidine-based adjuvant chemotherapy. Our findings may facilitate clinical trials on biomarker-oriented postoperative adjuvant chemotherapy for patients with locally advanced GC.

Translocon-associated protein subunit SSR3 determines and predicts susceptibility to paclitaxel in breast cancer and glioblastoma

PURPOSE

Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for glioblastomas (GBMs). Despite the widespread use of PTX for breast cancer, and the initiative to repurpose this drug for gliomas, there are no predictive biomarkers to inform which patients will likely benefit from this therapy.

EXPERIMENTAL DESIGN

To identify predictive biomarkers for susceptibility to PTX, we performed a genome-wide CRISPR knock-out (KO) screen using human glioma cells. The genes whose KO was most enriched in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort using progression-free survival.

RESULTS

Combination of CRISPR screen results with outcomes from taxane-treated breast cancer patients led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with susceptibility to PTX in breast cancer cells, glioma cells and in multiple intracranial glioma xenografts models. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. Mechanistically, SSR3 confers susceptibility to PTX through regulation of phosphorylation of ER stress sensor IRE1α.

CONCLUSION

Our hypothesis generating study showed SSR3 as a putative biomarker for susceptibility to PTX, warranting its prospective clinical validation.

Emergence of Nanotechnology as a Powerful Cavalry against Triple-Negative Breast Cancer (TNBC)

Triple-negative breast cancer (TNBC) is considered one of the un-manageable types of breast cancer, involving devoid of estrogen, progesterone, and human epidermal growth factor receptor 2 (HER 2) receptors. Due to their ability of recurrence and metastasis, the management of TNBC remains a mainstay challenge, despite the advancements in cancer therapies. Conventional chemotherapy remains the only treatment regimen against TNBC and suffers several limitations such as low bioavailability, systemic toxicity, less targetability, and multi-drug resistance. Although various targeted therapies have been introduced to manage the hardship of TNBC, they still experience certain limitations associated with the survival benefits. The current research thus aimed at developing and improving the strategies for effective therapy against TNBC. Such strategies involved the emergence of nanoparticles. Nanoparticles are designated as nanocavalries, loaded with various agents (drugs, genes, etc.) to battle the progression and metastasis of TNBC along with overcoming the limitations experienced by conventional chemotherapy and targeted therapy. This article documents the treatment regimens of TNBC along with their efficacy towards different subtypes of TNBC, and the various nanotechnologies employed to increase the therapeutic outcome of FDA-approved drug regimens.

Molecular Signatures of Tumour and Its Microenvironment for Precise Quantitative Diagnosis of Oral Squamous Cell Carcinoma: An International Multi-Cohort Diagnostic Validation Study

BACKGROUND

Heterogeneity in oral potentially malignant disorder (OPMD) poses a problem for accurate prognosis that impacts on treatment strategy and patient outcome. A holistic assessment based on gene expression signatures from both the tumour cells and their microenvironment is necessary to provide a more precise prognostic assessment than just tumour cell signatures alone.

METHODS

We reformulated our previously established multigene qPCR test, quantitative Malignancy Index Diagnostic System (qMIDS) with new genes involved in matrix/stroma and immune modulation of the tumour microenvironment. An algorithm calculates and converts a panel of 16 gene mRNA expression levels into a qMIDS index to quantify risk of malignancy for each sample.

RESULTS

The new qMIDS^V2 assay was validated in a UK oral squamous cell carcinoma (OSCC) cohort (n = 282) of margin and tumour core samples demonstrating significantly better diagnostic performance (AUC = 0.945) compared to previous qMIDS^V1 (AUC = 0.759). Performance of qMIDS^V2 were independently validated in Chinese (n = 35; AUC = 0.928) and Indian (n = 95; AUC = 0.932) OSCC cohorts. Further, 5-year retrospective analysis on an Indian dysplastic lesion cohort (n = 30) showed that qMIDS^V2 was able to significantly differentiate between lesions without transformation and those with malignant transformation.

CONCLUSIONS

This study validated a novel multi-gene qPCR test on a total of 535 tissue specimens from UK, China and India, demonstrating a rapid minimally invasive method that has a potential application for dysplasia risk stratification. Further study is required to establish if qMIDS^V2 could be used to improve OPMD patient management, guide treatment strategy and reduce oral cancer burden.

High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer

PURPOSE

Although the DNA repair mechanism is important in preventing carcinogenesis, its activation in established cancer cells may support their proliferation and aggravate cancer progression. RAD51 cooperates with BRCA2 and is essential in the homologous recombination of DNA repair. To this end, we hypothesized that RAD51 gene expression is associated with cancer cell proliferation and poor prognosis of breast cancer (BC) patients.

METHODS

A total of 8515 primary BC patients with transcriptome and clinical data from 17 independent cohorts were analyzed. The median value was used to divide each cohort into high and low RAD51 expression groups.

RESULTS

High RAD51 expression enriched the DNA repair gene set and was correlated with DNA repair-related genes. Nottingham histological grade, Ki67 expression and cell proliferation-related gene sets (E2F Targets, G2M Checkpoint and Myc Targets) were all significantly associated with the high RAD51 BC group. RAD51 expression was positively correlated with Homologous Recombination Deficiency, as well as both mutational burden and neoantigens that accompanied a higher infiltration of immune cells. Primary BC with lymph node metastases was associated with high expression of RAD51 in two cohorts. There was no strong correlation between RAD51 expression and drug sensitivity in cell lines, and RAD51 expression was lower after the neoadjuvant chemotherapy compared to before the treatment. High RAD51 BC was associated with poor prognosis consistently in three independent cohorts.

CONCLUSION

RAD51 gene expression is associated with aggressive cancer biology, cancer cell proliferation, and poor survival in breast cancer.

Multi-omic machine learning predictor of breast cancer therapy response

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

Ceramide Transfer Protein (CERT): An Overlooked Molecular Player in Cancer

Sphingolipids are a class of essential lipids implicated in constructing cellular membranes and regulating nearly all cellular functions. Sphingolipid metabolic network is centered with the ceramide-sphingomyelin axis. Ceramide is well-recognized as a pro-apoptotic signal; while sphingomyelin, as the most abundant type of sphingolipids, is required for cell growth. Therefore, the balance between these two sphingolipids can be critical for cancer cell survival and functioning. Ceramide transfer protein (CERT) dictates the ratio of ceramide to sphingomyelin within the cell. It is the only lipid transfer protein that specifically delivers ceramide from the endoplasmic reticulum to the Golgi apparatus, where ceramide serves as the substrate for sphingomyelin synthesis. In the past two decades, an increasing body of evidence has suggested a critical role of CERT in cancer, but much more intensive efforts are required to draw a definite conclusion. Herein, we review all research findings of CERT, focusing on its molecular structure, cellular functions and implications in cancer. This comprehensive review of CERT will help to better understand the molecular mechanism of cancer and inspire to identify novel druggable targets.

Triple-Negative Breast Cancer: Breast Tumors With an Identity Crisis

ABSTRACT

Triple-negative breast cancer (TNBC) is pathologically defined by lack of expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 amplification and portends an aggressive clinical course with worse outcomes compared with other breast cancers. Until recently, standard treatment options consisted of sequential cytotoxic chemotherapies for both early and metastatic disease. Advances in sequencing technology have led to the identification of 4 main subtypes of TNBC based on recurrent genetic alterations, transcriptional patterns, and molecular features: basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), and luminal androgen receptor (LAR). Frequent alterations found in DNA damage response pathways, germline and somatic BRCA1/2 genes, PI3K signaling pathways, and the presence of androgen receptors and infiltrating immune cells could serve as actionable targets to optimize treatments and improve outcomes for patients with TNBC. Recent approvals for immune checkpoint inhibitors and the antibody-drug conjugate, sacituzumab govitecan-hziy, for advanced TNBC illustrate the advances in treatment that can result from these molecular discoveries. This review will explore the molecular subtypes of TNBC and their distinct characteristics, as well as highlight the molecular features and potential "drivers" that have been identified as promising targets for new treatment strategies.

STARD3: A Prospective Target for Cancer Therapy

Cancer is one of the major causes of death in developed countries and current therapies are based on surgery, chemotherapeutic agents, and radiation. To overcome side effects induced by chemo- and radiotherapy, in recent decades, targeted therapies have been proposed in second and even first lines. Targeted drugs act on the essential pathways involved in tumor induction, progression, and metastasis, basically all the hallmark of cancers. Among emerging pathways, the cholesterol metabolic pathway is a strong candidate for this purpose. Cancer cells have an accelerated metabolic rate and require a continuous supply of cholesterol for cell division and membrane renewal. Steroidogenic acute regulatory related lipid transfer (START) proteins are a family of proteins involved in the transfer of lipids and some of them are important in non-vesicular cholesterol transportation within the cell. The alteration of their expression levels is implicated in several diseases, including cancers. In this review, we report the latest discoveries on StAR-related lipid transfer protein domain 3 (STARD3), a member of the START family, which has a potential role in cancer, focusing on the structural and biochemical characteristics and mechanisms that regulate its activity. The role of the STARD3 protein as a molecular target for the development of cancer therapies is also discussed. As STARD3 is a key protein in the cholesterol movement in cancer cells, it is of interest to identify inhibitors able to block its activity.

Unveiling Novel Therapeutic Drug Targets and Prognostic Markers of Triple Negative Breast Cancer

Triple negative breast cancer represents multiple genomic and transcriptomic heterogeneities. Genetic and epigenetic changes emerging in TNBC help it in acquiring resistance against immunological response. Distant metastasis, lack of clinically targeted therapies and prognostic markers make it the most aggressive form of breast cancer. In this review, we showed that driver alterations in targeted genes AR, ERR, TIL, TAM, miRNA, mTOR and immunosuppressive cytokines are predominantly involved in complicating TNBC by inducing cell proliferation, invasion and metastasis, and by inhibiting apoptosis. The role of node status, cathepsin-D, Ki-67 index, CD3+TIL, BRCA1 promoter methylation value and p53 as an efficient prognostic factor have also been studied to predict the disease free and overall survival rate in TNBC patients. The present review article is an attempt to gain an insight with a new vision on the etiology of TNBC, its treatment strategies and prognostic marker to identify the outcome of standard therapies and to re-design future treatment strategies to provide maximum benefit to patients.

Triple Negative Breast Cancer: A Mountain Yet to Be Scaled Despite the Triumphs

Metastatic progression and tumor recurrence pertaining to TNBC are certainly the leading cause of breast cancer-related mortality; however, the mechanisms underlying TNBC chemoresistance, metastasis, and tumor relapse remain somewhat ambiguous. TNBCs show 77% of the overall 4-year survival rate compared to other breast cancer subtypes (82.7 to 92.5%). TNBC is the most aggressive subtype of breast cancer, with chemotherapy being the major approved treatment strategy. Activation of ABC transporters and DNA damage response genes alongside an enrichment of cancer stem cells and metabolic reprogramming upon chemotherapy contribute to the selection of chemoresistant cells, majorly responsible for the failure of anti-chemotherapeutic regime. These selected chemoresistant cells further lead to distant metastasis and tumor relapse. The present review discusses the approved standard of care and targetable molecular mechanisms in chemoresistance and provides a comprehensive update regarding the recent advances in TNBC management.

Relevance of Membrane Contact Sites in Cancer Progression

Membrane contact sites (MCS) are typically defined as areas of proximity between heterologous or homologous membranes characterized by specific proteins. The study of MCS is considered as an emergent field that shows how crucial organelle interactions are in cell physiology. MCS regulate a myriad of physiological processes such as apoptosis, calcium, and lipid signaling, just to name a few. The membranal interactions between the endoplasmic reticulum (ER)–mitochondria, the ER–plasma membrane, and the vesicular traffic have received special attention in recent years, particularly in cancer research, in which it has been proposed that MCS regulate tumor metabolism and fate, contributing to their progression. However, as the therapeutic or diagnostic potential of MCS has not been fully revisited, in this review, we provide recent information on MCS relevance on calcium and lipid signaling in cancer cells and on its role in tumor progression. We also describe some proteins associated with MCS, like CERT, STIM1, VDAC, and Orai, that impact on cancer progression and that could be a possible diagnostic marker. Overall, these information might contribute to the understanding of the complex biology of cancer cells.

Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple‐negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple‐negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response‐probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER‐positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple‐negative breast cancer data and, for each patient, we calculated a response probability score (TNBC‐RPS). Our results indicate that the TNBC‐RPS achieved the highest accuracy for predicting neoadjuvant chemotherapy response compared to previously proposed 143 gene signatures. When combined with additional clinical factors, the TNBC‐RPS achieved a high prediction accuracy for triple‐negative breast cancer patients, which was comparable to the prediction accuracy of Oncotype DX and MammaPrint in ER‐positive patients. In conclusion, the TNBC‐RPS accurately predicts neoadjuvant chemotherapy response in triple‐negative breast cancer patients and has the potential to be clinically used to aid physicians in stratifying patients for more effective neoadjuvant chemotherapy.

Triple-negative breast cancer molecular subtyping and treatment progress

Triple-negative breast cancer (TNBC), a specific subtype of breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER-2), has clinical features that include high invasiveness, high metastatic potential, proneness to relapse, and poor prognosis. Because TNBC tumors lack ER, PR, and HER2 expression, they are not sensitive to endocrine therapy or HER2 treatment, and standardized TNBC treatment regimens are still lacking. Therefore, development of new TNBC treatment strategies has become an urgent clinical need. By summarizing existing treatment regimens, therapeutic drugs, and their efficacy for different TNBC subtypes and reviewing some new preclinical studies and targeted treatment regimens for TNBC, this paper aims to provide new ideas for TNBC treatment.

Ultrasound-Mediated Long-Circulating Nanopolymer Delivery of Therapeutic siRNA and Antisense MicroRNAs Leads to Enhanced Paclitaxel Sensitivity in Epithelial Ovarian Cancer Chemotherapy

Epithelial ovarian cancer (EOC) is one of the leading malignant tumors that seriously threaten women's health. The development of new drugs or increasing the sensitivities of current chemotherapy drugs is critically needed. The purpose of this study was to assess the synergistic effects of two silencing RNAs [salt-inducible kinase 2 (SIK2) siRNA and antisense-microRNA21 (anti-miR21)] encapsulated in long-circulating folate-lipid-poly(lactic-co-glycolic acid) (PLGA) hybrid nanopolymers (FaLPHNPs) administered using an ultrasound- and microbubble (US-MB)-mediated approach to sensitize human EOC xenografts to paclitaxel (PTX). In the in vitro assays, this lipid-PLGA hybrid nanopolymer exhibited an extended circulation profile (t_1/2: ∼8.5 h); US-MB-mediated complementary delivery of FaLPHNPs resulted in a significant reduction in EOC cell (OVCR3, A2780, and SKOV3) proliferation. In vivo, there was a 2.5-fold increase (p < 0.05) in RNA delivery in EOC xenografts, which resulted in a notable inhibition of tumor growth compared with that in the non-ultrasound-mediated and PTX alone-treated controls. We validated the therapeutic roles of SIK2, the target gene in treating advanced ovarian cancer, and anti-miR21 by evaluating the significant inhibition of tumor growth upon SIK2 silencing and inhibition of endogenous miR21 function. In summary, the results of this study revealed that US-MB-mediated codelivery of SIK2 siRNA, and anti-miR21 encapsulated in a folate-lipid-PLGA hybrid polymer nanoparticle could significantly improve the sensitivity of EOC tumors to PTX and is a highly effective approach for treating EOC in complementary experiments. Further research of this strategy could lead to better treatment results for patients with EOC.

Sphingolipid-Transporting Proteins as Cancer Therapeutic Targets

The understanding of the role of sphingolipid metabolism in cancer has tremendously increased in the past ten years. Many tumors are characterized by imbalances in sphingolipid metabolism. In many cases, disorders of sphingolipid metabolism are also likely to cause or at least promote cancer. In this review, sphingolipid transport proteins and the processes catalyzed by them are regarded as essential components of sphingolipid metabolism. There is much to suggest that these processes are often rate-limiting steps for metabolism of individual sphingolipid species and thus represent potential target structures for pharmaceutical anticancer research. Here, we summarize empirical and biochemical data on different proteins with key roles in sphingolipid transport and their potential role in cancer.

Clinical intelligence: New machine learning techniques for predicting clinical drug response

Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensitivity outcomes, which in turn results in lesser time spent and lower cost associated with identifying effective drug candidates. Although technological advances in high-throughput drug screening in cells led to the generation of a substantial amount of relevant data, the analysis of such data would be a challenging task. There is a critical need for advanced machine learning (ML) algorithms to generate accurate predictions of clinical drug response. A major goal of this work is to provide advanced ML tools to data analysts, who would in turn build prediction calculators to be incorporated into intelligent clinical decision support systems. Such innovative tools could be used to enhance patient-care, among other uses. To achieve this goal, we develop new ML techniques, including a transfer learning approach coupled with or without a boosting technique. Experimental results on real clinical data pertaining to breast cancer, multiple myeloma, and triple-negative cancer patients demonstrate the effectiveness and superiority of the proposed approaches compared to baseline approaches, including existing transfer learning methods.

Sphingolipid metabolism and drug resistance in ovarian cancer

Despite progress in understanding molecular aberrations that contribute to the development and progression of ovarian cancer, virtually all patients succumb to drug resistant disease at relapse. Emerging data implicate bioactive sphingolipids and regulation of sphingolipid metabolism as components of response to chemotherapy or development of resistance. Increases in cytosolic ceramide induce apoptosis in response to therapy with multiple classes of chemotherapeutic agents. Aberrations in sphingolipid metabolism that accelerate the catabolism of ceramide or that prevent the production and accumulation of ceramide contribute to resistance to standard of care platinum- and taxane-based agents. The aim of this review is to highlight current literature and research investigating the influence of the sphingolipids and enzymes that comprise the sphingosine-1-phosphate pathway on the progression of ovarian cancer. The focus of the review is on the utility of sphingolipid-centric therapeutics as a mechanism to circumvent drug resistance in this tumor type.

The miR-644a/CTBP1/p53 axis suppresses drug resistance by simultaneous inhibition of cell survival and epithelial-mesenchymal transition in breast cancer

Tumor cells develop drug resistance which leads to recurrence and distant metastasis. MicroRNAs are key regulators of tumor pathogenesis; however, little is known whether they can sensitize cells and block metastasis simultaneously. Here, we report miR-644a as a novel inhibitor of both cell survival and EMT whereby acting as pleiotropic therapy-sensitizer in breast cancer. We showed that both miR-644a expression and its gene signature are associated with tumor progression and distant metastasis-free survival. Mechanistically, miR-644a directly targets the transcriptional co-repressor C-Terminal Binding Protein 1 (CTBP1) whose knock-outs by the CRISPR-Cas9 system inhibit tumor growth, metastasis, and drug resistance, mimicking the phenotypes induced by miR-644a. Furthermore, downregulation of CTBP1 by miR-644a upregulates wild type- or mutant-p53 which acts as a 'molecular switch' between G1-arrest and apoptosis by inducing cyclin-dependent kinase inhibitor 1 (p21, CDKN1A, CIP1) or pro-apoptotic phorbol-12-myristate-13-acetate-induced protein 1 (Noxa, PMAIP1), respectively. Interestingly, an increase in mutant-p53 by either overexpression of miR-644a or downregulation of CTBP1 was enough to shift this balance in favor of apoptosis through upregulation of Noxa. Notably, p53-mutant patients, but not p53-wild type ones, with high CTBP1 have a shorter survival suggesting that CTBP1 could be a potential prognostic factor for breast cancer patients with p53 mutations. Overall, re-activation of the miR-644a/CTBP1/p53 axis may represent a new strategy for overcoming both therapy resistance and metastasis.

Triple negative breast cancer: shedding light onto the role of pi3k/akt/mtor pathway

Breast cancer is one of the most widespread carcinoma and one of the main causes of cancer-related death worldwide, especially in women aged between 35 and 75 years. Among the different subtypes, triple negative breast cancer (TNBC) is characterized by the total absence of the estrogen-receptor (ER) and progesteron-receptor (PR) expression as well as the lack of human epidermal growth factor receptor 2 (HER2) overexpression or gene amplification. These biological characteristics confer to TNBC a higher aggressiveness and relapse risk along with poorer prognosis compared to other subtypes. Indeed, 5-years survival rate is still low and almost all patients die, despite any adjuvant treatment which at moment represents the heading pharmacological approach. To date, several clinical trials have been designed to investigate the potential role of some molecular markers, such as VEGF, EGFR, Src and mTOR, for targeted treatments in TNBC. In fact, many inhibitors of the PI3K/AKT/mTOR pathway, frequently de-regulated in TNBC, are acquiring a growing interest and several inhibitors are in preclinical development or already in early phase clinical trials. In this Review, we investigated the role of the PI3K/AKT/mTOR pathway in TNBC patients, by summarizing the molecular features that led to the distinction of different histotypes of TNBC. Furthermore, we provided an overview of the inhibition mechanisms of the mTOR and PI3K/AKT signaling pathways, highlighting the importance of integrating biological and clinical data for the development of mTOR inhibitors in order to implement targeted therapies for TNBC patients.

Independent evaluation of a FOXM1-based quantitative malignancy diagnostic system (qMIDS) on head and neck squamous cell carcinomas

The forkhead box M1 (FOXM1) transcription factor gene has been implicated in almost all human cancer types. It would be an ideal biomarker for cancer detection but, to date, its translation into a cancer diagnostic tool is yet to materialise. The quantitative Malignancy Index Diagnostic System (qMIDS) was the first FOXM1 oncogene-based diagnostic test developed for quantifying squamous cell carcinoma aggressiveness. The test was originally validated using head and neck squamous cell carcinomas (HNSCC) from European patients. The HNSCC gene expression signature across geographical and ethnic differences is unknown. This is the first study evaluated the FOXM1-based qMIDS test using HNSCC specimens donated by ethnic Chinese patients. We tested 50 Chinese HNSCC patients and 18 healthy subjects donated 68 tissues in total. qMIDS scores from the Chinese cohort were compared with the European datasets (n = 228). The median ± SD scores for the Chinese cohort were 1.13 ± 0.66, 4.02 ± 1.66 and 5.83 ± 3.13 in healthy oral tissues, adjacent tumour margin and HNSCC core tissue, respectively. Diagnostic test efficiency between the Chinese and European datasets was almost identical. Consistent with previous European data, qMIDS scores for HNSCC samples were not influenced by gender or age. The degree of HNSCC differentiation, clinical stage and lymphatic metastasis status were found to be correlated with qMIDS scores. This study provided the first evidence that the pathophysiology of HNSCC was molecularly indistinguishable between the Chinese and European specimens. The qMIDS test robustly quantifies a universal FOXM1-driven oncogenic program, at least in HNSCC, which transcends ethnicity, age, gender and geographic origins.

Novel targets for paclitaxel nano formulations: Hopes and hypes in triple negative breast cancer

Triple negative breast cancer is defined as one of the utmost prevailing breast cancers worldwide, possessing an inadequate prognosis and treatment option limited to chemotherapy and radiotherapy, creating a challenge for researchers as far as developing a specific targeted therapy is concerned. The past research era has shown several promising outcomes for TNBC such as nano-formulations of the chemotherapeutic agents already used for the management of the malignant tumor. Taking a glance at paclitaxel nano formulations, it has been proven beneficial in several researches in the past decade; nevertheless its solubility is often a challenge to scientists in achieving success. We have henceforth discussed the basic heterogeneity of triple negative breast cancer along with the current management options as well as a brief outlook on pros and cons of paclitaxel, known as the most widely used chemotherapeutic agent for the treatment of the disease. We further analyzed the need of nanotechnology pertaining to the problems encountered with the current paclitaxel formulations available discussing the strategic progress in various nano-formulations till date taking into account the basic research strategies required in terms of solubility, permeability, physicochemical properties, active and passive targeting. A thorough review in recent advances in active targeting for TNBC was carried out whereby the various ligands which are at present finding its way into TNBC research such as hyaluronic acid, folic acid, transferrin, etc. were discussed. These ligands have specific receptor affinity to TNBC tumor cells hence can be beneficial for novel drug targeting approaches. Conversely, there are currently several novel strategies in the research pipeline whose targeting ligands have not yet been studied. Therefore, we reviewed upon the numerous novel receptor targets along with the respective nano-formulation aspects which have not yet been fully researched upon and could be exemplified as outstanding target strategies for TNBC which is currently an urgent requirement.

NETBAGs: a network-based clustering approach with gene signatures for cancer subtyping analysis

AIM

To evaluate gene signature and network-based approach for cancer subtyping and classification.

MATERIALS & METHODS

Here we introduced NETwork Based clustering Approach with Gene signatures (NETBAGs) algorithm, which clustered samples based on gene signatures and identified molecular markers based on their significantly expressed gene network profiles.

RESULTS

Applying NETBAGs to multiple independent breast cancer datasets, we demonstrated that the clustering results were highly associated with the clinical subtypes and clearly revealed the genomic diversity of breast cancer samples.

CONCLUSION

NETBAGs algorithm is able to classify samples by their genomic signatures into clinically significant phenotypes so that potential biomarkers can be identified. The approach may contribute to cancer research and clinical study of complex diseases.

How Taxol/paclitaxel kills cancer cells

Taxol (generic name paclitaxel) is a microtubule-stabilizing drug that is approved by the Food and Drug Administration for the treatment of ovarian, breast, and lung cancer, as well as Kaposi's sarcoma. It is used off-label to treat gastroesophageal, endometrial, cervical, prostate, and head and neck cancers, in addition to sarcoma, lymphoma, and leukemia. Paclitaxel has long been recognized to induce mitotic arrest, which leads to cell death in a subset of the arrested population. However, recent evidence demonstrates that intratumoral concentrations of paclitaxel are too low to cause mitotic arrest and result in multipolar divisions instead. It is hoped that this insight can now be used to develop a biomarker to identify the ∼50% of patients that will benefit from paclitaxel therapy. Here I discuss the history of paclitaxel and our recently evolved understanding of its mechanism of action.

Gene signature-guided dasatinib therapy in metastatic breast cancer

PURPOSE

Dasatinib has limited single-agent activity in unselected patients with metastatic breast cancer. Several gene signatures predictive of dasatinib response in vitro have been reported. The purpose of this three-arm, phase II study was to prospectively assess the utility of three previously published gene signatures to select patients with clinical benefit from dasatinib.

EXPERIMENTAL DESIGN

Patients with metastatic breast cancer underwent biopsy for gene expression profiling in an academic CLIA laboratory; those who were positive for any one of three predictive gene signatures (dasatinib sensitivity signature, SRC pathway activity signature, and dasatinib target index) received dasatinib 100 mg orally daily. The three marker-defined cohorts were analyzed separately, using early stopping rules for futility.

RESULTS

Ninety-seven patients were enrolled, 93 underwent biopsy, and 80% of the biopsies were sufficient for molecular testing. Thirty patients were positive for at least one signature and received treatment. Only 1 patient experienced clinical benefit and had stable disease over 300 days. All three arms were closed early for futility. There was one serious biopsy-related adverse event (hematoma and pain following a liver biopsy). There were no unexpected toxicities from dasatinib.

CONCLUSION

None of the three predictive gene signatures, although supported by preclinical evidence, defined tumors clinically sensitive to dasatinib as a single agent.

Predicting response to preoperative chemotherapy agents by identifying drug action on modeled microRNA regulation networks

Identifying patients most responsive to specific chemotherapy agents in neoadjuvant settings can help to maximize the benefits of treatment and minimize unnecessary side effects. Metagene approaches that predict response based on gene expression signatures derived from an associative analysis of clinical data can identify chance associations caused by the heterogeneity of a tumor, leading to reproducibility issues in independent validations. In this study, to incorporate information from drug mechanisms of action, we explore the potential of microRNA regulation networks as a new feature space for identifying predictive markers. We introduce a measure we term the CoMi (Context-specific-miRNA-regulation) pattern to represent a descriptive feature of the miRNA regulation network in the transcriptome. We examine whether the modifications to the CoMi pattern on specific biological processes are a useful representation of drug action by predicting the response to neoadjuvant Paclitaxel treatment in breast cancer and show that the drug counteracts the CoMi network dysregulation induced by tumorigenesis. We then generate a quantitative testbed to investigate the ability of the CoMi pattern to distinguish FDA approved breast cancer drugs from other FDA approved drugs not related to breast cancer. We also compare the ability of the CoMi and metagene methods to predict response to neoadjuvant Paclitaxel treatment in clinical cohorts. We find the CoMi method outperforms the metagene method, achieving area under curve (AUC) values of 0.78 and 0.66 respectively. Furthermore, several of the predicted CoMi features highlight the network-based mechanism of drug resistance. Thus, our study suggests that explicitly modeling the drug action using network biology provides a promising approach for predictive marker discovery.

Tumor histological subtyping determined by hormone receptors and HER2 status defines different pathological complete response and outcome to dose-dense neoadjuvant chemotherapy in breast cancer patients

PURPOSE

To assess the impact in pathological complete response (pCR) and outcome of two dose-dense neoadjuvant chemotherapy (DDNC) regimens among different histological subtypes determined by hormonal receptor (HR) and HER2 status in breast cancer patients.

METHODS

A total of 127 breast cancer patients were treated with DDNC in two prospective studies. A: adriamycin 40 mg/m(2) on day (d) 1 plus paclitaxel 150 mg/m(2) and gemcitabine 2,000 mg/m(2) on d2 for six cycles (n = 54). B: epirubicin 90 mg/m(2), cyclophosphamide 600 mg/m(2) on d1 for three cycles, followed by paclitaxel 150 mg/m(2) and gemcitabine 2,500 mg/m(2) on d1 ± trastuzumab according to HER2 status (n = 73). Histological subtypes of breast cancer were 49 % HR+/HER2-, 17.5 % HR+/HER2+, 13.5 % HR-/HER2+ and 20 % HR-/HER2-.

RESULTS

pCR (absence of invasive cells in breast and lymph node) was achieved in 35 patients (28 %). The pCR rate was significantly different between histological subtypes: HR+/HER2- (9 %), HR+/HER2+ (23 %), HR-/HER2+ (50 %), HR-/HER2- (56 %) (p < 0.001). The median follow-up was 81 months (r: 15-150 months). HR-/HER2- tumor subtype had a significantly worse DFS compared to HR+/HER2- (p = 0.02), RH+/HER2+ (p = 0.04) and HR-/HER2+ tumor subtypes (p = 0.02). HR-/HER2- tumor subtype had a significantly shorter OS compared to HR+/HER2- (p = 0.007), RH+/HER2+ (p = 0.05), and HR-/HER2+ (p = 0.03) tumor subtypes. However, no significant difference was observed in DFS and OS among HR-/HER2- tumors that achieved a pCR.

CONCLUSIONS

HR-/HER2- and HR-/HER2+ subtypes had a high pCR rate to DDNC. HR-/HER2- tumors had a worse outcome compared to other tumor subtypes but no significant difference was observed among HR-/HER2- tumors that achieved a pCR.

Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients

Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER)–negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-alpha (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. Here we describe in details the contents and quality controls for the gene expression and clinical data associated with the study published by Desmedt and colleagues in the Journal of Clinical Oncology in 2011 (Desmedt et al., 2011). We also provide R code to easily access the data and perform the quality controls and basic analyses relevant to this dataset.

Predictive value of sphingosine kinase 1 expression in neoadjuvant treatment of breast cancer

PURPOSE

Sphingolipids play important roles in apoptosis and cell proliferation. Sphingosine kinase 1 (SphK1) expression has a prognostic impact in primary breast cancer, but its predictive value is currently unknown.

METHODS

A total of 112 breast cancer specimens from a prospective neoadjuvant chemotherapy trial (GeparDuo) were studied. Using tissue microarrays of pre-treatment core cut biopsies, we determined the expression of SphK1 by immunohistochemistry. The upper quartile of the cohort according to an immune reactive score of SphK1 was used as cutoff for high expression.

RESULTS

We observed a larger number of samples with high SphK1 expression among ER-negative cancers (36.8 vs. 20.5 % among ER-positive cancers; Fisher test p = 0.073). Eighteen of the 112 patients demonstrated a pathological complete response. A significant predictive value for pathological complete response was observed for ER negativity (p = 0.003), young age (p = 0.037), and high tumor grade (p = 0.049). An increased pCR rate was observed in tumors with high SphK1 expression within the luminal subtype (26.7 vs. 5.8 %; Fisher test p = 0.040). No significant difference in survival was detected according to SphK1 expression.

CONCLUSIONS

Our results suggest that SphK1 may be a predictive factor for pCR after neoadjuvant treatment in luminal type breast cancers and warrants further investigation.

Reactivation of estrogen receptor α by vorinostat sensitizes mesenchymal-like triple-negative breast cancer to aminoflavone, a ligand of the aryl hydrocarbon receptor

OBJECTIVE

Aminoflavone (AF) acts as a ligand of the aryl hydrocarbon receptor (AhR). Expression of estrogen receptor α (ERα) and AhR-mediated transcriptional induction of CYP1A1 can sensitize breast cancer cells to AF. The objective of this study was to investigate the combined antitumor effect of AF and the histone deacetylase inhibitor vorinostat for treating mesenchymal-like triple-negative breast cancer (TNBC) as well as the underlying mechanisms of such treatment.

METHODS

In vitro antiproliferative activity of AFP464 (AF prodrug) in breast cancer cell lines was evaluated by MTS assay. In vitro, the combined effect of AFP464 and vorinostat on cell proliferation was assessed by the Chou-Talalay method. In vivo, antitumor activity of AFP464, given alone and in combination with vorinostat, was studied using TNBC xenograft models. Knockdown of ERα was performed using specific, small-interfering RNA. Western blot, quantitative RT-PCR, immunofluorescence, and immunohistochemical staining were performed to study the mechanisms underlying the combined antitumor effect.

RESULTS

Luminal and basal A subtype breast cancer cell lines were sensitive to AFP464, whereas basal B subtype or mesenchymal-like TNBC cells were resistant. Vorinostat sensitized mesenchymal-like TNBC MDA-MB-231 and Hs578T cells to AFP464. It also potentiated the antitumor activity of AFP464 in a xenograft model using MDA-MB-231 cells. In vitro and in vivo mechanistic studies suggested that vorinostat reactivated ERα expression and restored AhR-mediated transcriptional induction of CYP1A1.

CONCLUSION

The response of breast cancer cells to AF or AFP464 was associated with their gene expression profile. Vorinostat sensitized mesenchymal-like TNBC to AF, at least in part, by reactivating ERα expression and restoring the responsiveness of AhR to AF.

Independent validation of a model using cell line chemosensitivity to predict response to therapy

BACKGROUND

Methods using cell line microarray and drug sensitivity data to predict patients' chemotherapy response are appealing, but groups may be reluctant to release details to preserve intellectual property. Here we describe a case study to validate predictions while treating the methods as a "black box."

METHODS

Medical Prognosis Institute (MPI) constructed cell-line-derived sensitivity scores (SSs) and combined scores (CSs) that incorporate clinical variables. MD Anderson researchers evaluated their predictions. We searched the Gene Expression Omnibus (GEO) to identify validation datasets, and we performed statistical evaluation of the agreement between prediction and clinical observation.

RESULTS

We identified 3 suitable datasets: GSE16446 (n = 120; binary outcome), GSE17920 (n = 130; binary outcome), and GSE10255 (n = 161; continuous and time-to-event outcomes). The SS was statistically significantly associated with primary treatment responses for all studies (GSE16446: P = .02; GSE17920: P = .02; GSE10255: P = .02). Dichotomized SSs performed no better than chance for GSE16446 and GSE17920, and categorized SSs did not predict disease-free survival (GSE10255). SSs sometimes improved on predictions using clinical variables (GSE16446: P = .05; GSE17920: P = .31; GSE10255: P = .045), but gains were limited (95% confidence intervals for GSE16446 and GSE17920 include 0). The CS did not predict treatment response for GSE16446 (P = .55), but it did for GSE17920 (P < .001). Coefficients of clinical variables provided by MPI for CSs agree with estimates for GSE17920 better than estimates for GSE16446.

CONCLUSIONS

Model predictions were better than chance in all three datasets. However, these scores added little to existing clinical predictors; statistically significant contributions were likely to be too small to change clinical practice. These findings suggest that discovering better predictors will require both cell line data and a clinical training dataset of patient samples.