Genetic Biomarkers of Sorafenib Response in Patients with Hepatocellular Carcinoma.

The identification of biomarkers for predicting inter-individual sorafenib response variability could allow hepatocellular carcinoma (HCC) patient stratification. SNPs in angiogenesis- and drug absorption, distribution, metabolism, and excretion (ADME)-related genes were evaluated to identify new potential predictive biomarkers of sorafenib response in HCC patients. Five known SNPs in angiogenesis-related genes, including VEGF-A, VEGF-C, HIF-1a, ANGPT2, and NOS3, were investigated in 34 HCC patients (9 sorafenib responders and 25 non-responders). A subgroup of 23 patients was genotyped for SNPs in ADME genes. A machine learning classifier method was used to discover classification rules for our dataset. We found that only the VEGF-A (rs2010963) C allele and CC genotype were significantly associated with sorafenib response. ADME-related gene analysis identified 10 polymorphic variants in ADH1A (rs6811453), ADH6 (rs10008281), SULT1A2/CCDC101 (rs11401), CYP26A1 (rs7905939), DPYD (rs2297595 and rs1801265), FMO2 (rs2020863), and SLC22A14 (rs149738, rs171248, and rs183574) significantly associated with sorafenib response. We have identified a genetic signature of predictive response that could permit non-responder/responder patient stratification. Angiogenesis- and ADME-related genes correlation was confirmed by cumulative genetic risk score and network and pathway enrichment analysis. Our findings provide a proof of concept that needs further validation in follow-up studies for HCC patient stratification for sorafenib prescription.

Exploiting DNA Ligase III addiction of multiple myeloma by flavonoid Rhamnetin.

BACKGROUND: DNA ligases are crucial for DNA repair and cell replication since they catalyze the final steps in which DNA breaks are joined. DNA Ligase III (LIG3) exerts a pivotal role in Alternative-Non-Homologous End Joining Repair (Alt-NHEJ), an error-prone DNA repair pathway often up-regulated in genomically unstable cancer, such as Multiple Myeloma (MM). Based on the three-dimensional (3D) LIG3 structure, we performed a computational screening to identify LIG3-targeting natural compounds as potential candidates to counteract Alt-NHEJ activity in MM. METHODS: Virtual screening was conducted by interrogating the Phenol Explorer database. Validation of binding to LIG3 recombinant protein was performed by Saturation Transfer Difference (STD)-nuclear magnetic resonance (NMR) experiments. Cell viability was analyzed by Cell Titer-Glo assay; apoptosis was evaluated by flow cytometric analysis following Annexin V-7AAD staining. Alt-NHEJ repair modulation was evaluated using plasmid re-joining assay and Cytoscan HD. DNA Damage Response protein levels were analyzed by Western blot of whole and fractionated protein extracts and immunofluorescence analysis. The mitochondrial DNA (mtDNA) copy number was determined by qPCR. In vivo activity was evaluated in NOD-SCID mice subcutaneously engrafted with MM cells. RESULTS: Here, we provide evidence that a natural flavonoid Rhamnetin (RHM), selected by a computational approach, counteracts LIG3 activity and killed Alt-NHEJ-dependent MM cells. Indeed, Nuclear Magnetic Resonance (NMR) showed binding of RHM to LIG3 protein and functional experiments revealed that RHM interferes with LIG3-driven nuclear and mitochondrial DNA repair, leading to significant anti-MM activity in vitro and in vivo. CONCLUSION: Taken together, our findings provide proof of concept that RHM targets LIG3 addiction in MM and may represent therefore a novel promising anti-tumor natural agent to be investigated in an early clinical setting.

The New Microtubule-Targeting Agent SIX2G Induces Immunogenic Cell Death in Multiple Myeloma.

Microtubule-targeting agents (MTAs) are effective drugs for cancer treatment. A novel diaryl [1,2]oxazole class of compounds binding the colchicine site was synthesized as cis-restricted-combretastatin-A-4-analogue and then chemically modified to have improved solubility and a wider therapeutic index as compared to vinca alkaloids and taxanes. On these bases, a new class of tricyclic compounds, containing the [1,2]oxazole ring and an isoindole moiety, has been synthetized, among which SIX2G emerged as improved MTA. Several findings highlighted the ability of some chemotherapeutics to induce immunogenic cell death (ICD), which is defined by the cell surface translocation of Calreticulin (CALR) via dissociation of the PP1/GADD34 complex. In this regard, we computationally predicted the ability of SIX2G to induce CALR exposure by interacting with the PP1 RVxF domain. We then assessed both the potential cytotoxic and immunogenic activity of SIX2G on in vitro models of multiple myeloma (MM), which is an incurable hematological malignancy characterized by an immunosuppressive milieu. We found that the treatment with SIX2G inhibited cell viability by inducing G2/M phase cell cycle arrest and apoptosis. Moreover, we observed the increase of hallmarks of ICD such as CALR exposure, ATP release and phospho-eIF2α protein level. Through co-culture experiments with immune cells, we demonstrated the increase of (i) CD86 maturation marker on dendritic cells, (ii) CD69 activation marker on cytotoxic T cells, and (iii) phagocytosis of tumor cells following treatment with SIX2G, confirming the onset of an immunogenic cascade. In conclusion, our findings provide a framework for further development of SIX2G as a new potential anti-MM agent.

Exploiting MYC-induced PARPness to target genomic instability in multiple myeloma.

Multiple Myeloma (MM) is a hematologic malignancy strongly characterized by genomic instability, which promotes disease progression and drug resistance. Since we previously demonstrated that LIG3-dependent repair is involved in the genomic instability, drug resistance and survival of MM cells, we here investigated the biological relevance of PARP1, a driver component of Alternative-Non Homologous End Joining (Alt-NHEJ) pathway, in MM. We found a significant correlation between higher PARP1 mRNA expression and poor prognosis of MM patients. PARP1 knockdown or its pharmacological inhibition by Olaparib impaired MM cells viability in vitro and was effective against in vivo xenografts of human MM. Anti-proliferative effects induced by PARP1-inhibition were correlated to increase of DNA double-strand breaks, activation of DNA Damage Response (DDR) and finally apoptosis. Importantly, by comparing a gene expression signature of PARP inhibitors (PARPi) sensitivity to our plasma cell dyscrasia (PC) gene expression profiling (GEP), we identified a subset of MM patients which could benefit from PARP inhibitors. In particular, Gene Set Enrichment Analysis (GSEA) suggested that high MYC expression correlates to PARPi sensitivity in MM. Indeed, we identified MYC as promoter of PARP1-mediated repair in MM and, consistently, we demonstrate that cytotoxic effects induced by PARP inhibition are mostly detectable on MYC-proficient MM cells. Taken together, our findings indicate that MYC-driven MM cells are addicted to PARP1 Alt-NHEJ repair, which represents therefore a druggable target in this still incurable disease.

Error-prone DNA repair pathways as determinants of immunotherapy activity: an emerging scenario for cancer treatment.

Defects in DNA repair machinery play a critical role in the pathogenesis and progression of human cancer. When they occur, the tumor cells activate error-prone mechanisms which lead to genomic instability and high mutation rate. These defects represent, therefore, a cancer Achilles'heel which could be therapeutically exploited by the use of DNA damage response inhibitors. Moreover, experimental and clinical evidence indicates that DNA repair deregulation has a pivotal role also in promoting immune recognition and immune destruction of cancer cells. Indeed, immune checkpoint inhibitors have received regulatory approval in tumors characterized by high genomic instability, such as melanomas and lung cancer. Here, we discuss how deregulation of DNA repair, through activation of error-prone mechanisms, increases immune activation against cancer. Finally, we address the potential strategies to use DNA repair components as biomarkers and/or therapeutic targets to empower immune-oncology treatment of human cancer.

Pharmacogenomics: Challenges and Future.

Over the last few decades, the implementation of pharmacogenomics (PGx) in clinical practice has improved tailored drug prescriptions [...].

Polymorphisms and Pharmacogenomics of NQO2: The Past and the Future.

The flavoenzyme N-ribosyldihydronicotinamide (NRH):quinone oxidoreductase 2 (NQO2) catalyzes two-electron reductions of quinones. NQO2 contributes to the metabolism of biogenic and xenobiotic quinones, including a wide range of antitumor drugs, with both toxifying and detoxifying functions. Moreover, NQO2 activity can be inhibited by several compounds, including drugs and phytochemicals such as flavonoids. NQO2 may play important roles that go beyond quinone metabolism and include the regulation of oxidative stress, inflammation, and autophagy, with implications in carcinogenesis and neurodegeneration. NQO2 is a highly polymorphic gene with several allelic variants, including insertions (I), deletions (D) and single-nucleotide (SNP) polymorphisms located mainly in the promoter, but also in other regulatory regions and exons. This is the first systematic review of the literature reporting on NQO2 gene variants as risk factors in degenerative diseases or drug adverse effects. In particular, hypomorphic 29 bp I alleles have been linked to breast and other solid cancer susceptibility as well as to interindividual variability in response to chemotherapy. On the other hand, hypermorphic polymorphisms were associated with Parkinson's and Alzheimer's disease. The I and D promoter variants and other NQO2 polymorphisms may impact cognitive decline, alcoholism and toxicity of several nervous system drugs. Future studies are required to fill several gaps in NQO2 research.

The impact of PARP inhibitors in the whole scenario of ovarian cancer management: A systematic review and network meta-analysis.

BACKGROUND: Carboplatin is still the cornerstone of the first-line treatment in advanced Epithelial Ovarian Cancer (aEOC) management and the clinical response to platinum-derived agents remains the major predictor of long-term outcomes. PATIENT AND METHODS: We aimed to identify the best treatment of the aEOC in terms of efficacy and safety, considering all treatment phases. A systematic literature search has been done to compare all treatments in aEOC population. Randomized trials with available survival and safety data published in the 2011-2022 timeframe were enclosed. Only trials reporting the BRCA or HRD (Homologous Recombination Deficiency) status were considered. DATA EXTRACTION AND SYNTHESIS: A ranking of treatment schedules on the progression-free survival (PFS) endpoint was performed. The random-effect model was used to elaborate and extract data. The Network Meta-Analysis (NMA) by Bayesian model was performed by STATA v17. Data on PFS were extracted in terms of Hazard ratio with relative confidence intervals. RESULTS: This NMA involved 18 trials for a total of 9105 patients. Within 12 treatment groups, we performed 3 different sensitivity analyses including "all comers" Intention to Treat (ITT) population, BRCA-mutated (BRCAm), and HRD subgroups, respectively. Considering the SUCRA-reported cumulative PFS probabilities, we showed that in the ITT population, the inferred best treatment was niraparib plus bevacizumab with a SUCRA of 96.7. In the BRCAm subgroup, the best SUCRA was for olaparib plus chemotherapy (96,9). The HRD population showed an inferred best treatment for niraparib plus bevacizumab (SUCRA 98,4). Moreover, we reported a cumulative summary of PARPi toxicity, in which different 3-4 grade toxicity profiles were observed, despite the PARPi "class effect" in terms of efficacy. CONCLUSIONS: Considering all aEOC subgroups, the best therapeutical option was identified as PARPi plus chemotherapy and/or antiangiogenetic agents, suggesting the relevance of combinatory approaches based on molecular profile. This work underlines the potential value of "chemo-free" regimens to prolong the platinum-free interval (PFI).

Identification of ADME genes polymorphic variants linked to trastuzumab-induced cardiotoxicity in breast cancer patients: Case series of mono-institutional experience.

BACKGROUND: Long-term survival induced by anticancer treatments discloses emerging frailty among breast cancer (BC) survivors. Trastuzumab-induced cardiotoxicity (TIC) is reported in at least 5% of HER2+BC patients. However, TIC mechanism remains unclear and predictive genetic biomarkers are still lacking. Interaction between systemic inflammation, cytokine release and ADME genes in cancer patients might contribute to explain mechanisms underlying individual susceptibility to TIC and drug response variability. We present a single institution case series to investigate the potential role of genetic variants in ADME genes in HER2+BC patients TIC experienced. METHODS: We selected data related to 40 HER2+ BC patients undergone to DMET genotyping of ADME constitutive variant profiling, with the aim to prospectively explore their potential role in developing TIC. Only 3 patients ("case series"), who experienced TIC, were compared to 37 "control group" matched patients cardiotoxicity-sparing. All patients underwent to left ventricular ejection fraction (LVEF) evaluation at diagnosis and during anti-HER2 therapy. Each single probe was clustered to detect SNPs related to cardiotoxicity. RESULTS: In this retrospective analysis, our 3 cases were homogeneous in terms of clinical-pathological characteristics, trastuzumab-based treatment and LVEF decline. We identified 9 polymorphic variants in 8 ADME genes (UGT1A1, UGT1A6, UGT1A7, UGT2B15, SLC22A1, CYP3A5, ABCC4, CYP2D6) potentially associated with TIC. CONCLUSION: Real-world TIC incidence is higher compared to randomized clinical trials and biomarkers with potential predictive value aren't available. Our preliminary data, as proof of concept, could suggest a predictive role of pharmacogenomic approach in the identification of cardiotoxicity risk biomarkers for anti-HER2 treatment.

Autophagy and neuroprotection in astrocytes exposed to 6-hydroxydopamine is negatively regulated by NQO2: relevance to Parkinson's disease.

Dopaminergic degeneration is a central feature of Parkinson's disease (PD), but glial dysfunction may accelerate or trigger neuronal death. In fact, astrocytes play a key role in the maintenance of the blood-brain barrier and detoxification. 6-hydroxydopamine (6OHDA) is used to induce PD in rodent models due to its specific toxicity to dopaminergic neurons, but its effect on astrocytes has been poorly investigated. Here, we show that 6OHDA dose-dependently impairs autophagy in human U373 cells and primary murine astrocytes in the absence of cell death. LC3II downregulation was observed 6 to 48 h after treatment. Interestingly, 6OHDA enhanced NRH:quinone oxidoreductase 2 (NQO2) expression and activity in U373 cells, even if 6OHDA turned out not to be its substrate. Autophagic flux was restored by inhibition of NQO2 with S29434, which correlated with a partial reduction in oxidative stress in response to 6OHDA in human and murine astrocytes. NQO2 inhibition also increased the neuroprotective capability of U373 cells, since S29434 protected dopaminergic SHSY5Y cells from 6OHDA-induced cell death when cocultured with astrocytes. The toxic effects of 6OHDA on autophagy were attenuated by silencing NQO2 in human cells and primary astrocytes from NQO2-/- mice. Finally, the analysis of Gene Expression Omnibus datasets showed elevated NQO2 gene expression in the blood cells of early-stage PD patients. These data support a toxifying function of NQO2 in dopaminergic degeneration via negative regulation of autophagy and neuroprotection in astrocytes, suggesting a potential pharmacological target in PD.

Pembrolizumab plus lenvatinib in advanced endometrial cancer: case report and systematic review of lung toxicity.

Background: The optimal strategy for the treatment of recurrent and/or advanced endometrial cancer is still undefined. Recently, despite the lack of any predictive biomarker, the combination of pembrolizumab with lenvatinib has improved survival outcomes. We here report the long-term management of lung toxicity in a patient with endometrial cancer, and we critically review the current therapeutic options for this disease. Results: A patient with heavily pretreated endometrial cancer took pembrolizumab plus lenvatinib for 1 year, achieving a persistent partial response with a time to treatment failure of 18 months, despite relevant lung toxicity that did not affect the remarkable overall clinical benefit. A systematic review of this combination underlines the efficacy outcome despite toxicity. Interestingly, the literature review on lung toxicity suggested the role of anti-angiogenetic agents in the pathogenesis of lung cavitation, probably related to direct treatment activity, and disclosed a potential radiological sign predictive of the activity of anti-angiogenetic agents. Conclusion: We underline the efficacy of pembrolizumab plus lenvatinib in the current treatment landscape of endometrial cancer, underscoring the relevance of a correct management of toxicity.

The First-In-Class Anti-AXL×CD3ε Pronectin™-Based Bispecific T-Cell Engager Is Active in Preclinical Models of Human Soft Tissue and Bone Sarcomas.

Sarcomas are heterogeneous malignancies with limited therapeutic options and a poor prognosis. We developed an innovative immunotherapeutic agent, a first-in-class Pronectin™-based Bispecific T-Cell Engager (pAXL×CD3ε), for the targeting of AXL, a TAM family tyrosine kinase receptor highly expressed in sarcomas. AXL expression was first analyzed by flow cytometry, qRT-PCR, and Western blot on a panel of sarcoma cell lines. The T-cell-mediated pAXL×CD3ε cytotoxicity against sarcoma cells was investigated by flow cytometry, luminescence assay, and fluorescent microscopy imaging. The activation and degranulation of T cells induced by pAXL×CD3ε were evaluated by flow cytometry. The antitumor activity induced by pAXL×CD3ε in combination with trabectedin was also investigated. In vivo activity studies of pAXL×CD3ε were performed in immunocompromised mice (NSG), engrafted with human sarcoma cells and reconstituted with human peripheral blood mononuclear cells from healthy donors. Most sarcoma cells showed high expression of AXL. pAXL×CD3ε triggered T-lymphocyte activation and induced dose-dependent T-cell-mediated cytotoxicity. The combination of pAXL×CD3ε with trabectedin increased cytotoxicity. pAXL×CD3ε inhibited the in vivo growth of human sarcoma xenografts, increasing the survival of treated mice. Our data demonstrate the antitumor efficacy of pAXL×CD3ε against sarcoma cells, providing a translational framework for the clinical development of pAXL×CD3ε in the treatment of human sarcomas, aggressive and still-incurable malignancies.

TERRA G-quadruplex stabilization as a new therapeutic strategy for multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a hematologic malignancy characterized by high genomic instability, and telomere dysfunction is an important cause of acquired genomic alterations. Telomeric repeat-containing RNA (TERRA) transcripts are long non-coding RNAs involved in telomere stability through the interaction with shelterin complex. Dysregulation of TERRAs has been reported across several cancer types. We recently identified a small molecule, hit 17, which stabilizes the secondary structure of TERRA. In this study, we investigated in vitro and in vivo anti-MM activities of hit 17. METHODS: Anti-proliferative activity of hit 17 was evaluated in different MM cell lines by cell proliferation assay, and the apoptotic process was analyzed by flow cytometry. Gene and protein expressions were detected by RT-qPCR and western blotting, respectively. Microarray analysis was used to analyze the transcriptome profile. The effect of hit 17 on telomeric structure was evaluated by chromatin immunoprecipitation. Further evaluation in vivo was proceeded upon NCI-H929 and AMO-1 xenograft models. RESULTS: TERRA G4 stabilization induced in vitro dissociation of telomeric repeat-binding factor 2 (TRF2) from telomeres leading to the activation of ATM-dependent DNA damage response, cell cycle arrest, proliferation block, and apoptotic death in MM cell lines. In addition, up-regulation of TERRA transcription was observed upon DNA damage and TRF2 loss. Transcriptome analysis followed by gene set enrichment analysis (GSEA) confirmed the involvement of the above-mentioned processes and other pathways such as E2F, MYC, oxidative phosphorylation, and DNA repair genes as early events following hit 17-induced TERRA stabilization. Moreover, hit 17 exerted anti-tumor activity against MM xenograft models. CONCLUSION: Our findings provide evidence that targeting TERRA by hit 17 could represent a promising strategy for a novel therapeutic approach to MM.

Safety and activity of the first-in-class locked nucleic acid (LNA) miR-221 selective inhibitor in refractory advanced cancer patients: a first-in-human, phase 1, open-label, dose-escalation study.

BACKGROUND: We developed a 13-mer locked nucleic acid (LNA) inhibitor of miR-221 (LNA-i-miR-221) with a full phosphorothioate (PS)-modified backbone. This agent downregulated miR-221, demonstrated anti-tumor activity against human xenografts in mice, and favorable toxicokinetics in rats and monkeys. Allometric interspecies scaling allowed us to define the first-in-class LNA-i-miR-221 safe starting dose for the clinical translation. METHODS: In this first-in-human, open-label, dose-escalation phase 1 trial, we enrolled progressive cancer patients (aged ≥ 18 years) with ECOG 0-2 into 5 cohorts. The treatment cycle was based on a 30-min IV infusion of LNA-i-miR-221 on 4 consecutive days. Three patients within the first cohort were treated with 2 cycles (8 infusions), while 14 patients were treated with a single course (4 infusions); all patients were evaluated for phase 1 primary endpoint. The study was approved by the Ethics Committee and Regulatory Authorities (EudraCT 2017-002615-33). RESULTS: Seventeen patients received the investigational treatment, and 16 were evaluable for response. LNA-i-miR-221 was well tolerated, with no grade 3-4 toxicity, and the MTD was not reached. We recorded stable disease (SD) in 8 (50.0%) patients and partial response (PR) in 1 (6.3%) colorectal cancer case (total SD + PR: 56.3%). Pharmacokinetics indicated non-linear drug concentration increase across the dose range. Pharmacodynamics demonstrated concentration-dependent downregulation of miR-221 and upregulation of its CDKN1B/p27 and PTEN canonical targets. Five mg/kg was defined as the recommended phase II dose. CONCLUSIONS: The excellent safety profile, the promising bio-modulator, and the anti-tumor activity offer the rationale for further clinical investigation of LNA-i-miR-221 (ClinTrials.Gov: NCT04811898).

DMET-analyzer: automatic analysis of Affymetrix DMET data.

BACKGROUND: Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs. RESULTS: We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding the analysis of clinical datasets produced in the University Hospital of Catanzaro, Italy. CONCLUSION: DMET Analyzer is a novel tool able to automatically analyse data produced by the DMET-platform in case-control association studies. Using such tool user may avoid wasting time in the manual execution of multiple statistical tests avoiding possible errors and reducing the amount of time needed for a whole experiment. Moreover annotations and the direct link to external databases may increase the biological knowledge extracted. The system is freely available for academic purposes at: https://sourceforge.net/projects/dmetanalyzer/files/

Microarray Data Analysis Protocol.

Microarrays are broadly used in the omic investigation and have several areas of applications in biology and medicine, providing a significant amount of data for a single experiment. Different kinds of microarrays are available, identifiable by characteristics such as the type of probes, the surface used as support, and the method used for the target detection. To better deal with microarray datasets, the development of microarray data analysis protocols simple to use as well as able to produce accurate reports, and comprehensible results arise. The object of this paper is to provide a general protocol showing how to choose the best software tool to analyze microarray data, allowing to efficiently figure out genomic/pharmacogenomic biomarkers.

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients.

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

Integration of DNA Microarray with Clinical and Genomic Data.

DNA microarrays have been widely employed to understand cancer development. This technology is able to measure expression levels of a large numbers of genes or to genotype multiple regions of a genome in a massively parallel experiment. In addition, the detection of methylation patterns and gene copy number variations are also performed. Clinicians began to apply these findings in personalized medicine for the selection of cancer therapy according to the individual's cancer genomic profile. Because cancer is a complex disease it is of great value to integrate microarray data with genomic and clinical data. Here, we presented an overview of DNA microarray technology and discuss about benefits and challenging of microarray data integration.

Risk Alleles for Multiple Myeloma Susceptibility in ADME Genes.

The cause of multiple myeloma (MM) remains largely unknown. Several pieces of evidence support the involvement of genetic and multiple environmental factors (i.e., chemical agents) in MM onset. The inter-individual variability in the bioactivation, detoxification, and clearance of chemical carcinogens such as asbestos, benzene, and pesticides might increase the MM risk. This inter-individual variability can be explained by the presence of polymorphic variants in absorption, distribution, metabolism, and excretion (ADME) genes. Despite the high relevance of this issue, few studies have focused on the inter-individual variability in ADME genes in MM risk. To identify new MM susceptibility loci, we performed an extended candidate gene approach by comparing high-throughput genotyping data of 1936 markers in 231 ADME genes on 64 MM patients and 59 controls from the CEU population. Differences in genotype and allele frequencies were validated using an internal control group of 35 non-cancer samples from the same geographic area as the patient group. We detected an association between MM risk and ADH1B rs1229984 (OR = 3.78; 95% CI, 1.18-12.13; p = 0.0282), PPARD rs6937483 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), SLC28A1 rs8187737 (OR = 11.33; 95% CI, 1.43-89.59; p = 0.005), SLC28A2 rs1060896 (OR = 6.58; 95% CI, 1.42-30.43; p = 0.0072), SLC29A1 rs8187630 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), and ALDH3A2 rs72547554 (OR = 2.46; 95% CI, 0.64-9.40; p = 0.0293). The prognostic value of these genes in MM was investigated in two public datasets showing that shorter overall survival was associated with low expression of ADH1B and SLC28A1. In conclusion, our proof-of-concept findings provide novel insights into the genetic bases of MM susceptibility.

A Prognostic and Carboplatin Response Predictive Model in Ovarian Cancer: A Mono-Institutional Retrospective Study Based on Clinics and Pharmacogenomics.

Carboplatin is the cornerstone of ovarian cancer (OC) treatment, while platinum-response, dependent on interindividual variability, is the major prognostic factor for long-term outcomes. This retrospective study was focused on explorative search of genetic polymorphisms in the Absorption, Distribution, Metabolism, Excretion (ADME) genes for the identification of biomarkers prognostic/predictive of platinum-response in OC patients. Ninety-two advanced OC patients treated with carboplatin-based therapy were enrolled at our institution. Of these, we showed that 72% of patients were platinum-sensitive, with a significant benefit in terms of OS (p = 0.001). We identified an inflammatory-score with a longer OS in patients with lower scores as compared to patients with the maximum score (p = 0.001). Thirty-two patients were genotyped for 1931 single nucleotide polymorphisms (SNPs) and five copy number variations (CNVs) by the DMET Plus array platform. Among prognostic polymorphisms, we found a potential role of UGT2A1 both as a predictor of platinum-response (p = 0.01) and as prognostic of survival (p = 0.05). Finally, we identified 24 SNPs related to OS. UGT2A1 correlates to an "inflammatory-score" and retains a potential prognostic role in advanced OC. These data provide a proof of concept that warrants further validation in follow-up studies for the definition of novel biomarkers in this aggressive disease.