Loss of constitutive ABCB1 expression in breast cancer associated with worse prognosis

ABCB1 Regulates Immune Genes in Breast Cancer

Background

Resistance to standard chemotherapy is a critical problem for breast cancer patients. The ATP-binding cassette (ABC) superfamily transporters actively pump out drugs and play an important role in chemoresistance. ABCB1 (ABC subfamily B, member 1, also named as multidrug resistance protein 1, MDR1) and suppressive myeloid-derived suppressor cells (MDSCs) potentially involve in chemoresistance of breast cancer. The relationship between ABCB1 and immune genes in breast cancer has not been widely studied.

Methods

Microarray and RNA sequencing data were obtained from The Cancer Genome Atlas Breast Invasive Carcinoma in Genomic Data Commons Data Portal and Gene Expression Omnibus database. A patient-derived xenograft (PDX) model of HER2+ breast cancer was established to investigate the association between ABCB1 and immune genes in breast cancer.

Results

Expression of ABCB1 increased in doxorubicin-selected MCF-7/ADR cells. High expression of ABCB1 mRNA is correlated with lymph-node metastasis and worse overall survival in patients with breast cancer. ABCB1 is positively correlated with IL6, CSF1, CSF3, and PTGS2. In the HER2+ stage IIA breast cancer PDX model, both doxorubicin and paclitaxel suppressed growth of P2 tumors. IL6, CSF1, CSF3, and PTGS2 expression were suppressed by paclitaxel but not doxorubicin. Intrasplenic MDSCs, including CD11b+Ly6G+ and CD11b+Ly6C+ cells, were more abundant than intratumor MDSCs in PDX-carrying nude mice. Clinically, the patient developed cancer recurrence after adjuvant chemotherapy with doxorubicin-based regimen and was well controlled after paclitaxel-trastuzumab combined therapy.

Conclusion

ABCB1 was a poor predictor of HER2+ LN- breast cancer. Regulation of immune genes by ABCB1 contributed to cancer recurrence and treatment effect. The PDX model was suitable for investigation the expression of target genes and expansion of immune cells.

Molecular aspects of ABCB1 and ABCG2 in Gallbladder cancer and its clinical relevance

The function of ABC transporters in the body is manifold; such as maintenance of homeostasis, effect on multi-drug resistance and their role in tumor initiation & progression. Evidence pointing towards the direct or indirect role of ABC transporter genes in particular; ABCB1 and ABCG2 in cancer genesis is increasing. However, their role in gallbladder cancer is unexplored. Therefore, we investigated the methylation status and expression pattern of ABCB1 and ABCG2in gallbladder carcinogenesis. The methylation and expression study of ABCB1/MDR1 and ABCG2/BCRP was performed in tumour and normal fresh tissue samples collected from 61 histopathologically diagnosed gallbladder cancer patients. The methylation status was analysed by Methylation-Specific PCR and expression was determined by Real-Time PCR and Immunohistochemistry. Hypomethylation of ABCB1 and ABCG2 was found in 44 (72.13%) and 48 (78.6%) cases, respectively. ABCB1 hypomethylation pattern showed association with female patients (p = 0.040) and GradeII tumors (p = 0.036) while, ABCG2 hypomethylation was more frequent in early tumors (T1-T2). The mRNA expression ofABCB1 and ABCG2 was up-regulated in 33 (54.10%) and 41 (67.21%) patients with fold change of 4.7 and 5.5, respectively. The mRNA expression of both genes showed association with Grade II tumours and the increased fold change of ABCG2 was higher in (T1-T2) depth of invasion (p = 0.02) and Stage I-II disease (p = 0.08). The protein expression on IHC was strongly positive for ABCB1/MDR1and ABCG2/BCRP in 32 (52.46%) and 45 (73.77%) patients, respectively. The protein expression in ABCG2 showed association with patients age > 50 years (p = 0.04) and GradeII differentiation (p = 0.07). Interestingly, the hypomethylation of both the genes showed significant correlation with increased expression. ABCB1/MDR1 and ABCG2/BCRP hypomethylation and overexpression could have a potential role in gallbladder cancer tumorigenesis especially in early stages. The epigenetic change might be a plausible factor for altered gene expression of ABCB1 and ABCG2 in gallbladder cancer.

Construction of a three commitment points for S phase entry cell cycle model and immune-related ceRNA network to explore novel therapeutic options for psoriasis

While competing endogenous RNAs (ceRNAs) play pivotal roles in various diseases, the proliferation and differentiation of keratinocytes are becoming a research focus in psoriasis. Therefore, the three commitment points for S phase entry (CP1-3) cell cycle model has pointed to a new research direction in these areas. However, it is unclear what role ceRNA regulatory mechanisms play in the interaction between keratinocytes and the immune system in psoriasis. In addition, the ceRNA network-based screening of potential therapeutic agents for psoriasis has not been explored. Therefore, we used multiple bioinformatics approaches to construct a ceRNA network for psoriasis, identified CTGF as the hub gene, and constructed a ceRNA subnetwork, after which validation datasets authenticated the results' accuracy. Subsequently, we used multiple online databases and the single-sample gene-set enrichment analysis algorithm, including the CP1-3 cell cycle model, to explore the mechanisms accounting for the increased proliferation and differentiation of keratinocytes and the possible roles of the ceRNA subnetwork in psoriasis. Next, we performed cell cycle and cell trajectory analyses based on a single-cell RNA-seq dataset of psoriatic skin biopsies. We also used weighted gene co-expression network analysis and single-gene batch correlation analysis-based gene set enrichment analysis to explore the functions of CTGF. Finally, we used the Connectivity Map to identify MS-275 (entinostat) as a novel treatment for psoriasis, SwissTargetPrediction to predict drug targets, and molecular docking to investigate the minimum binding energy and binding sites of the drug to target proteins.

Impact of the ABCB1 Drug Resistance Gene on the Risk Factors of Patients with COVID-19 and Its Relationship with the Drugs Used

Objective

In the last two years progress was made in molecular, physio pathological understanding and the form of transmission of COVID-19, and different therapeutic strategies have been explored to deal with the situation of the pandemic. However, the evaluation of certain genes that participate in the metabolism and transport of these drugs has not been fully explored. A lack of response to treatment and a lower survival have been observed that may be due to the presence of the ABCB1 drug resistance gene. Our research group analyzed whether the expression levels of the ABCB1 gene are associated with comorbidities, treatments, overall survival and risk of death in patients with severe COVID-19.

Methods

The expression levels of the ABCB1 gene were analyzed by RT-qPCR in 61 patients diagnosed with COVID-19. The association between the levels of expression, the risk variables and different treatments were determined by the Chi-Square test and the Fisher’s exact test. Global Survival (GS) was determined by the Kaplan–Meier method. The impact of high levels of expression and the risk of death was performed by odds ratio.

Results

The different risk variables showed that patients with either high or absent levels of ABCB1 gene expression presented a greater risk of death (OR 3.08, 95%, CI 1.02–9.26) as well as need for ventilatory support (OR 2.8, 95%, CI 0.98 −8.5). Patients with diabetes and COVID-19, treated with metformin, were associated with a lower risk of death (OR 1.11, 95%, CI 0.38–3.22). OS with respect to high or absent levels of expression of the ABCB1 gene was lower.

Conclusion

High levels or null expression of the ABCB1 gene are associated with a higher risk of death or progression of the disease, the use of metformin in patients with COVID-19 confers a lower risk of death.

Pleiotropic Roles of ABC Transporters in Breast Cancer

Chemotherapeutics are the mainstay treatment for metastatic breast cancers. However, the chemotherapeutic failure caused by multidrug resistance (MDR) remains a pivotal obstacle to effective chemotherapies of breast cancer. Although in vitro evidence suggests that the overexpression of ATP-Binding Cassette (ABC) transporters confers resistance to cytotoxic and molecularly targeted chemotherapies by reducing the intracellular accumulation of active moieties, the clinical trials that target ABCB1 to reverse drug resistance have been disappointing. Nevertheless, studies indicate that ABC transporters may contribute to breast cancer development and metastasis independent of their efflux function. A broader and more clarified understanding of the functions and roles of ABC transporters in breast cancer biology will potentially contribute to stratifying patients for precision regimens and promote the development of novel therapies. Herein, we summarise the current knowledge relating to the mechanisms, functions and regulations of ABC transporters, with a focus on the roles of ABC transporters in breast cancer chemoresistance, progression and metastasis.

Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast

BACKGROUND

There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE).

METHODS

Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2.

RESULTS

Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E-05; LOOCV AUC = 0.74, log-rank test P = 0.006).

CONCLUSION

Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.

The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes

ADME genes are a group of genes that are involved in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes within tumours is proposed to impact on cancer patient survival; however, this has not been systematically examined. In this study, our comprehensive analyses of pan-cancer datasets from the Cancer Genome Atlas (TCGA) revealed differential intratumoral expression profiles for ADME genes in 21 different cancer types. Most genes also showed high interindividual variability within cancer-specific patient cohorts. Using Kaplan-Meier plots and logrank tests, we showed that intratumoral expression levels of twenty of the thirty-two core ADME genes were associated with overall survival (OS) in these cancers. Of these genes, five showed significant association with unfavourable OS in three cancers, including SKCM (ABCC2, GSTP1), KIRC (CYP2D6, CYP2E1), PAAD (UGT2B7); sixteen showed significant associations with favourable OS in twelve cancers, including BLCA (UGT2B15), BRCA (CYP2D6), COAD (NAT1), HNSC (ABCB1), KIRC (ABCG2, CYP3A4, SLC22A2, SLC22A6), KIRP (SLC22A2), LIHC (CYP2C19, CYP2C8, CYP2C9, CYP3A5, SLC22A1), LUAD (SLC15A2), LUSC (UGT1A1), PAAD (ABCB1), SARC (ABCB1), and SKCM (ABCB1, DYPD). Overall, these data provide compelling evidence supporting ADME genes as prognostic biomarkers and potential therapeutic targets. We propose that intratumoral expression of ADME genes may impact cancer patient survival by multiple mechanisms that can include metabolizing/transporting anticancer drugs, activating anticancer drugs, and metabolizing/transporting a variety of endogenous molecules involved in metabolically fuelling cancer cells and/or controlling pro-growth signalling pathways.

New perspectives in triple-negative breast cancer therapy based on treatments with TGFβ1 siRNA and doxorubicin

Triple-negative breast cancer (TNBC), which accounts for 10-20% of all breast cancers, has the worst prognosis. Although chemotherapy treatment is a standard for TNBC, it lacks a specific target. Therefore, new therapeutic strategies are required to be investigated. In this study, a combined doxorubicin (DOX) and small interfering RNA (siRNA) therapy is proposed as therapeutic strategy for targeting TGFβ1 gene. Hs578T cell line is used as in vitro model for TNBC, wherein TGFβ1siRNA therapy is employed to enhance therapeutic effects. Cell proliferation rate is measured using an MTT test, and morphological alterations are assed using microscopically approached, while gene expression is determined by qRT-PCR analysis. The combined treatment of TGFβ1siRNA and DOX reduced levels of cell proliferation and mitochondrial activity and promoted the alteration of cell morphology (dark-field microscopy). DOX treatment caused downregulation of six genes and upregulation of another six genes. The combined effects of DOX and TGFβ1siRNA resulted in upregulation of 13 genes and downregulation of four genes. Silencing of TGFβ1 resulted in activation of cell death mechanisms in Hs578T cells, to potentiate the effects of DOX, but not in an additive manner, due to the activation of genes involved in resistance to therapy (ABCB1 and IL-6).

The impact of ABCB1 gene polymorphism and its expression on non-small-cell lung cancer development, progression and therapy - preliminary report

The ABCB1 gene belongs to ATP binding cassette (ABC) transporter genes that has been previously implicated in cancer progression and drug response. This study aimed to evaluate the association between the SNP 3435 and the expression of the ABCB1 gene in lung cancer patients in the Polish population in comparison to clinicopathological parameters and treatment. 150 RNA and 47 DNA samples were isolated from 49 lung cancer cases including both tissue samples and blood taken from the same patients at three time points: diagnosis, 100 days and one year after the surgical intervention. Qualitative and real-time PCR analysis of expression were done, also genotyping by PCR-RFLP. Mutant homozygous TT and allele T are present statistically significantly more frequently in the group of patients with lung cancer. There is no difference with expression level in lung cancer tissue and blood sample taken from the same patients before surgical treatment. On the basis of blood samples analysis it was observed that the expression level of ABCB1 mRNA was growing in time. Higher levels were marked after 100 days and one year after the surgical intervention. The complementary pharmacological treatment induced higher expression levels of ABCB1. The presented data suggest an important role of ABCB1 in lung cancer, the increasing level of ABCB1 mRNA which can be connected with induction of multidrug resistance mechanism is also significant, that observation must be confirmed in further analysis.

Gene Expression-Based Predictive Markers for Paclitaxel Treatment in ER+ and ER- Breast Cancer

One of the objectives of precision oncology is to identify patient’s responsiveness to a given treatment and prevent potential overtreatments through molecular profiling. Predictive gene expression biomarkers are a promising and practical means to this purpose. The overall response rate of paclitaxel drugs in breast cancer has been reported to be in the range of 20–60% and is in the even lower range for ER-positive patients. Predicting responsiveness of breast cancer patients, either ER-positive or ER-negative, to paclitaxel treatment could prevent individuals with poor response to the therapy from undergoing excess exposure to the agent. In this study, we identified six sets of gene signatures whose gene expression profiles could robustly predict nonresponding patients with precisions more than 94% and recalls more than 93% on various discovery datasets (n = 469 for the largest set) and independent validation datasets (n = 278), using the previously developed Multiple Survival Screening algorithm, a random-sampling-based methodology. The gene signatures reported were stable regardless of half of the discovery datasets being swapped, demonstrating their robustness. We also reported a set of optimizations that enabled the algorithm to train on small-scale computational resources. The gene signatures and optimized methodology described in this study could be used for identifying unresponsiveness in patients of ER-positive or ER-negative breast cancers.