Marisa Cañadas-Garre

PTEN and PI3K/AKT in non-small-cell lung cancer.

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. In the last years, the identification of activating EGFR mutations, conferring increased sensitivity and disease response to tyrosine kinase inhibitors, has changed the prospect of NSCLC patients. The PTEN/PI3K/AKT pathway regulates multiple cellular functions, including cell growth, differentiation, proliferation, survival, motility, invasion and intracellular trafficking. Alterations in this pathway, mainly PTEN inactivation, have been associated with resistance to EGFR-tyrosine kinase inhibitor therapy and lower survival in NSCLC patients. In this review, we will briefly discuss the main PTEN/PI3K/AKT pathway alterations found in NSCLC, as well as the cell processes regulated by PTEN/PI3K/AKT leading to tumorigenesis.

MET: a new promising biomarker in non-small-cell lung carcinoma.

Non-small-cell lung cancer (NSCLC) leads cancer-related deaths worldwide. Mutations in the kinase domain of the EGFR gene provide sensitivity to tyrosine kinase inhibitors (TKI) drugs. TKI show initial response rates over 75% in mutant EGFR-NSCLC patients, although most of these patients acquire resistance to EGFR inhibitors after therapy. EGFR-TKI resistance mechanisms include amplification in MET and its ligand, and also MET mutations. MET signaling dysregulation has been involved in tumor cell growth, survival, migration and invasion, angiogenesis and activation of several pathways, therefore representing an attractive target for anticancer drug development. In this review, we will discuss MET-related mechanisms of EGFR-TKI resistance in NSCLC, as well as the main drugs targeted to inhibit MET pathway.

Pharmacogenetic predictors of toxicity to platinum based chemotherapy in non-small cell lung cancer patients

Platinum-based chemotherapy is the standard treatment for NSCLC patients with EGFR wild-type, and as alternative to failure to EGFR inhibitors. However, this treatment is aggressive and most patients experience grade 3-4 toxicities. ERCC1, ERCC2, ERCC5, XRCC1, MDM2, ABCB1, MTHFR, MTR, SLC19A1, IL6 and IL16 gene polymorphisms may contribute to individual variation in toxicity to chemotherapy. The aim of this study was to evaluate the effect of these polymorphisms on platinum-based chemotherapy in NSCLC patients. A prospective cohorts study was conducted, including 141 NSCLC patients. Polymorphisms were analyzed by PCR Real-Time with Taqman(®) probes and sequencing. Patients with ERCC1 C118T-T allele (p=0.00345; RR=26.05; CI95%=4.33, 515.77) and ERCC2 rs50872-CC genotype (p=0.00291; RR=4.06; CI95%=1.66, 10.65) had higher risk of general toxicity for platinum-based chemotherapy. ERCC2 Asp312Asn G-alelle, ABCB1 C1236T-TT and the IL1B rs12621220-CT/TT genotypes conferred a higher risk to present multiple adverse events. The subtype toxicity analysis also revealed that ERCC2 rs50872-CC genotype (p=0.01562; OR=3.23; CI95%=1.29, 8.82) and IL16 rs7170924-T allele (p=0.01007; OR=3.19; CI95%=1.35, 7.97) were associated with grade 3-4 hematological toxicity. We did not found the influence of ERCC1 C8092A, ERCC2 Lys751Gln, ERCC2 Asp312Asn, ERCC5 Asp1104His, XRCC1 Arg194Trp, MDM2 rs1690924, ABCB1 C3435T, ABCB1 Ala893Ser/Thr, MTHFR A1298C, MTHFR C677T, IL1B rs1143623, IL1B rs16944, and IL1B rs1143627 on platinum-based chemotherapy toxicity. In conclusion, ERCC1 C118T, ERCC2 rs50872, ERCC2 Asp312Asn, ABCB1 C1236T, IL1B rs12621220 and IL16 rs7170924 polymorphisms may substantially act as prognostic factors in NSCLC patients treated with platinum-based chemotherapy.

Contribution of genetic factors to platinum-based chemotherapy sensitivity and prognosis of non-small cell lung cancer

Although platinum-based chemotherapy remains the standard treatment for advanced NSCLC patients, clinical outcomes are poor and most patients develop high-grade toxicities. Genetic factors, such as single nucleotide polymorphisms (SNPs) involved in platinum pharmacodynamics, metabolism and mechanism of action, may account for inter-individual differences shown in effectiveness and toxicity. Polymorphisms in genes involved in DNA repair and others such as PI3K/PTEN/AKT and TGF-β pathways have been demonstrated to be associated with response, survival and toxicity in advanced NSCLC patients treated with platinum-based chemotherapy. Other cellular processes, like DNA methylation and proliferation have been connected with clinical outcome for platinum-based chemotherapy regimens through folate metabolism and cytokine signaling. The influence of gene polymorphisms in the NER pathway on clinical outcome has been extensively investigated in advanced NSCLC patients treated with platinum-based chemotherapy but contradictory results have been reported. The most recent and thorough meta-analyses have failed to show an association between ERCC1 C118T/C8092A and ERCC5 rs1047768 polymorphisms and response to platinum based chemotherapy. However, other polymorphisms in ERCC2 (Lys751Gln and Asp312Asn) and ERCC5 (rs2094258 and rs2296147) and have been related with overall survival (OS) and progression-free survival (PFS), respectively. The Arg194Trp and Gln399Arg polymorphisms in XRCC1, have also been extensively investigated. Their effects seem to be dependent on ethnicity, and recent meta-analyses have confirmed an association with response in Asian but not in Caucasian patients. The influence on overall response rate (ORR) of the rs861539 polymorphism in XRCC3, part of (DSB) repair pathway, has also been confirmed in a meta-analysis. Finally, SNPs in genes coding proteins of the p53, PI3K, TGF-β, membrane transporters, gluthatione metabolism enzymes and cytokine pathways have been less extensively investigated. Some polymorphisms have been reported to be associated with toxicity or clinical outcome, but data generally come from a limited number of studies and need to be confirmed.

Genetic and clinical biomarkers of tocilizumab response in patients with rheumatoid arthritis

The aim of this study was to investigate the influence of clinical and genetic factors on response to tocilizumab (TCZ) response, remission, low disease activity (LDA) and DAS28 improvement. A retrospective cohort study in 79 RA patients treated with TCZ during 6/18 months of therapy was conducted. CD69(rs11052877), GALNT18(rs4910008), CLEC2D(rs1560011), KCNMB1(rs703505), ENOX1(rs9594987), rs10108210, and rs703297 gene polymorphisms, identified in a recent GWAS as putative predictors of TCZ response, were analysed. Variables independently associated to satisfactory EULAR response at 6 months were GALNT18-CC genotype (ORCC/T-:12.8; CI95%:1.5,108.7; p=0.02), CD69 gene polymorphism (ORAA/GG:17.2; CI95%:2.5,119.6; p=0.004) and lower number of previous biological therapy, BT (OR: 0.45; CI95%:0.3, 0.7; p=0.001). The factors independently associated to higher remission were lower number of previous BT (OR:0.56; CI95%:0.38, 0.82; p=0.003), and GALNT18 CC genotype (ORCT/CC:0.09; CI95%:0.02,0.45;p=0.004; ORTT/CC:0.14; CI95%:0.02,0.79; p=0.026). The A-allele of CD69 (ORA_/GG:6.68;CI95%:1.68,26.51;p=0.007) and lower number of previous BT (OR:0.50; CI95%:0.32,0.77; p=0.002) were independent factors capable to predict higher LDA rates at 6 months. Independent factors associated to higher improvement in DAS28 at 6 months were CD69-AA genotype (B=-0.56; CI95%:-1.09, -0.03; p=0.039), GALNT18-CC genotype (B=-0.88;CI95%:-1.49, -0.27; p=0.005), subcutaneous administration (B=1.03; CI95%:0.44,1.62; p=0.001) and higher baseline DAS28 (B=0.82; CI95%:0.59, 1.05; p=4.9×10(-10)). Lower number of previous BT was the only independent predictor of satisfactory EULAR response (OR:0.60; CI95%:0.34,0.88; p=0.010) and higher remission (OR:0.65; CI95%:0.46,0.93; p=0.018) at 18 months. The C-allele of GALNT18 (ORC-/TT:4.60; CI95%:1.16, 18.27; p=0.03) and lower number of previous BT (OR:0.47; CI95%:0.29,0.74; p=0.001) were independent factors capable to predict higher LDA rates at 18 months. In conclusion, RA patients treated with TCZ showed better EULAR response, remission, LDA and DAS28 improvement rates in patients carrying the GALNT18 C-allele or the CD69 A-allele, particularly when lower number of BT were previously administered.

Gene polymorphisms as predictors of response to biological therapies in psoriasis patients.

Psoriasis is a chronic inflammatory autoimmune skin disease, characterized by the formation of erythematous scaly plaques on the skin and joints. The therapies for psoriasis are mainly symptomatic and sometimes with poor response. Response among patients is very variable, especially with biological drugs (adalimumab, etarnecept, infliximab and ustekimumab). This variability may be partly explained by the effect of different genetic backgrounds. This has prompted the investigation of many genes, such as FCGR3A, HLA, IL17F, IL23R, PDE3A-SLCO1C1, TNFα and other associated genes, as potential candidates to predict response to the different biological drugs used for the treatment of psoriasis. In this article, we will review the influence of gene polymorphisms investigated to date on response to biological drugs in psoriasis patients.

Prediction of stable acenocoumarol dose by a pharmacogenetic algorithm.

Aim To develop an acenocoumarol (ACN) dosing algorithm for patients with atrial fibrillation or venous thromboembolism, considering the influence on the stable ACN dose of clinical factors and gene polymorphisms, including CYP2C9*2/*3, VKORC1, CYP4F2*3, ABCB1, APOE, CYP2C19*2/*17, and GGCX. Methods and results A retrospective observational study was carried out to obtain clinical and pharmacogenetic dose algorithms by multiple linear regression of results in a cohort of 134 patients under treatment with a stable ACN dose for atrial fibrillation or venous thromboembolism and to test them in an independent validation cohort of 30 patients. The pharmacogenetic dosing algorithm included CYP2C9, VKORC1, and APOE, which explained 56.6% of the variability in the stable ACN dose. Lower deviation from the stable dose and increased accuracy were shown by the pharmacogenetic algorithm, which correctly classified 67% of patients with a deviation of up to 20%. Conclusion The variability in the stable ACN dose was better explained by a pharmacogenetic algorithm including clinical and genetic factors (CYP2C9, VKORC1, and APOE) than by a clinical algorithm, providing a more accurate dosage prediction.

De novo resistance biomarkers to anti-HER2 therapies in HER2-positive breast cancer.

Therapies targeting HER2 receptor, overexpressed in 20% breast cancer (BC), improved prognosis, however ~62% patients experiment progression during the first year. Molecular mechanisms proposed to be responsible for this de novo resistance include HER2 modifications, defects in the antibody dependent cellular cytotoxicity or in cell arrest and apoptosis or alterations in HER2 signaling components. This article will review the influence of genetic markers investigated to date as cause of de novo resistance to HER2-targeted drugs in HER2-positive BC patients. Biomarkers like p95HER2, CCND1 and CDC25A have demonstrated clinical relevance and prognostic value in HER2-positive BC patients. However, the prognostic value of most biomarkers investigated to date, such as PIK3CA or AKT1, cannot be fully established yet.

Extrapolation of acenocoumarol pharmacogenetic algorithms

INTRODUCTION Acenocoumarol (ACN) has a narrow therapeutic range that is especially difficult to control at the start of its administration. Various dosing pharmacogenetic-guided dosing algorithms have been developed, but further work on their external validation is required. The aim of this study was to evaluate the extrapolation of pharmacogenetic algorithms for ACN as an alternative to the development of a specific algorithm for a given population. MATERIAL AND METHODS The predictive performance, deviation, accuracy, and clinical significance of five pharmacogenetic algorithms (EU-PACT, Borobia, Rathore, Markatos, Krishna Kumar) were compared in 189 stable ACN patients representing all indications for anticoagulant treatment. RESULTS The correlation between the dose predictions of the five pharmacogenetic models ranged from 7.7 to 70.6% and the percentage of patients with a correct prediction (deviation ≤20% from actual ACN dose) ranged from 5.9 to 40.7%. EU-PACT and Borobia pharmacogenetic dosing algorithms were the most accurate in our setting and evidenced the best clinical performance. CONCLUSIONS Among the five models studied, the EU-PACT and Borobia pharmacogenetic dosing algorithms demonstrated the best potential for extrapolation.

Molecular biomarkers in colorectal carcinoma.

Colorectal cancer is a tumor with increasing incidence which represents one of the first leading causes of death worldwide. Gene alterations described for colorectal cancer include genome instability (microsatellite and chromosomal instability), CpG islands methylator phenotype, microRNA, histone modification, protein biomarkers, gene mutations (RAS, BRAF, PI3K, TP53, PTEN) and polymorphisms (APC, CTNNB1, DCC). In this article, biomarkers with prognostic value commonly found in colorectal cancer will be reviewed.