Synergistic effect of antimetabolic and chemotherapy drugs in triple-negative breast cancer

The triple-negative breast cancer (TNBC) subtype comprises approximately 15% of all breast cancers and is associated with poor long-term outcomes. Classical chemotherapy remains the standard of treatment, with toxicity and resistance being major limitations. TNBC is a high metabolic group, and antimetabolic drugs are effective in inhibiting TNBC cell growth. We analyzed the combined effect of chemotherapy and antimetabolic drug combinations in MDA-MB-231, MDA-MB-468 and HCC1143 human TNBC cell lines. Cells were treated with each drug or with drug combinations at a range of concentrations to establish the half-maximal inhibitory concentrations (IC50). The dose-effects of each drug or drug combination were calculated, and the synergistic or antagonistic effects of drug combinations were defined. Chemotherapy and antimetabolic drugs exhibited growth inhibitory effects on TNBC cell lines. Antimetabolic drugs targeting the glycolysis pathway had a synergistic effect with chemotherapy drugs, and antiglycolysis drug combinations also had a synergistic effect. The use of these drug combinations could lead to new therapeutic strategies that reduce chemotherapy drug doses, decreasing their toxic effect, or that maintain the doses but enhance their efficacy by their synergistic effect with other drugsMaría I. Lumbreras-Herrera and Andrea Zapater-Moros are supported by Consejería de Educación e Investigación de la Comunidad de Madrid (IND2018/BMD-9262). Elena López-Camacho is supported by the Spanish Economy and Competitiveness Ministry (PTQ2018–009760). This work is supported by an unrestricted grant from Roch

A novel molecular analysis approach in colorectal cancer suggests new treatment opportunities

Colorectal cancer (CRC) is a molecular and clinically heterogeneous disease. In 2015, the Colorectal Cancer Subtyping Consortium classified CRC into four consensus molecular subtypes (CMS), but these CMS have had little impact on clinical practice. The purpose of this study is to deepen the molecular characterization of CRC. A novel approach, based on probabilistic graphical models (PGM) and sparse k-means–consensus cluster layer analyses, was applied in order to functionally characterize CRC tumors. First, PGM was used to functionally characterize CRC, and then sparse k-means–consensus cluster was used to explore layers of biological information and establish classifications. To this aim, gene expression and clinical data of 805 CRC samples from three databases were analyzed. Three different layers based on biological features were identified: adhesion, immune, and molecular. The adhesion layer divided patients into high and low adhesion groups, with prognostic value. The immune layer divided patients into immune-high and immunelow groups, according to the expression of immune-related genes. The molecular layer established four molecular groups related to stem cells, metabolism, the Wnt signaling pathway, and extracellular functions. Immune-high patients, with higher expression of immune-related genes and genes involved in the viral mimicry response, may benefit from immunotherapy and viral mimicry-related therapies. Additionally, several possible therapeutic targets have been identified in each molecular group. Therefore, this improved CRC classification could be useful in searching for new therapeutic targets and specific therapeutic strategies in CRC diseas

Utility of CYP2D6 copy number variants as prognostic biomarker in localized anal squamous cell carcinoma

Background: Anal squamous cell carcinoma (ASCC) is an infrequent tumor whose treatment has not changed since the 1970s. The aim of this study is the identification of biomarkers allowing personalized treatments and improvement of therapeutic outcomes. Methods: Forty-six paraffin tumor samples from ASCC patients were analyzed by whole-exome sequencing. Copy number variants (CNVs) were identified and their relation to disease-free survival (DFS) was studied and validated in an independent retrospective cohort of 101 ASCC patients from the Multidisciplinary Spanish Digestive Cancer Group (GEMCAD). GEMCAD cohort proteomics allowed assessing the biological features of these tumors. Results: On the discovery cohort, the median age was 61 years old, 50% were males, stages I/II/III: 3 (7%)/16 (35%)/27 (58%), respectively, median DFS was 33 months, and overall survival was 45 months. Twenty-nine genes whose duplication was related to DFS were identified. The most representative was duplications of the CYP2D locus, including CYP2D6, CYP2D7P, and CYP2D8P genes. Patients with CYP2D6 CNV had worse DFS at 5 years than those with two CYP2D6 copies (21% vs. 84%; p <.0002, hazard ratio [HR], 5.8; 95% confidence interval [CI], 2.7–24.9). In the GEMCAD validation cohort, patients with CYP2D6 CNV also had worse DFS at 5 years (56% vs. 87%; p =.02, HR = 3.6; 95% CI, 1.1–5.7). Mitochondria and mitochondrial cell-cycle proteins were overexpressed in patients with CYP2D6 CNV. Conclusions: Tumor CYP2D6 CNV identified patients with a significantly worse DFS at 5 years among localized ASCC patients treated with 5-fluorouracil, mitomycin C, and radiotherapy. Proteomics pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets for these high-risk patients. Plain Language Summary: Anal squamous cell carcinoma is an infrequent tumor whose treatment has not been changed since the 1970s. However, disease-free survival in late staged tumors is between 40% and 70%. The presence of an alteration in the number of copies of CYP2D6 gene is a biomarker of worse disease-free survival. The analysis of the proteins in these high-risk patients pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets. Therefore, the determination of the number of copies of CYP2D6 allows the identification of anal squamous carcinoma patients with a high-risk of relapse that could be redirected to a clinical trial. Additionally, this study may be useful to suggest new treatment strategies to increase current therapy efficacyIdiPAZ, Grant/Award Number: Jesús Antolín Garciarena Fellowship; European Proteomics Infrastructure Consortium, Grant/Award Number: 823839, Horizon 2020 Programm

Protein content of blood-derived extracellular vesicles: An approach to the pathophysiology of cerebral hemorrhage

Introduction: Extracellular vesicles (EVs) participate in cell-to-cell paracrine signaling and can be biomarkers of the pathophysiological processes underlying disease. In intracerebral hemorrhage, the study of the number and molecular content of circulating EVs may help elucidate the biological mechanisms involved in damage and repair, contributing valuable information to the identification of new therapeutic targets.Methods: The objective of this study was to describe the number and protein content of blood-derived EVs following an intracerebral hemorrhage (ICH). For this purpose, an experimental ICH was induced in the striatum of Sprague-Dawley rats and EVs were isolated and characterized from blood at baseline, 24 h and 28 days. The protein content in the EVs was analyzed by mass spectrometric data-dependent acquisition; protein quantification was obtained by sequential window acquisition of all theoretical mass spectra data and compared at pre-defined time points.Results: Although no differences were found in the number of EVs, the proteomic study revealed that proteins related to the response to cellular damage such as deubiquitination, regulation of MAP kinase activity (UCHL1) and signal transduction (NDGR3), were up-expressed at 24 h compared to baseline; and that at 28 days, the protein expression profile was characterized by a higher content of the proteins involved in healing and repair processes such as cytoskeleton organization and response to growth factors (COR1B) and the regulation of autophagy (PI42B).Discussion: The protein content of circulating EVs at different time points following an ICH may reflect evolutionary changes in the pathophysiology of the disease

Modelización computacional de las alteraciones metabólicas en cáncer de mama

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 28-03-2019La reprogramación del metabolismo es un proceso característico del cáncer, habiéndose descrito diferencias a nivel metabólico entre subtipos de cáncer de mama. El objetivo de este trabajo es, por un lado, caracterizar la respuesta de líneas celulares de cáncer de mama a dos fármacos con dianas metabólicas (metformina y rapamicina) y, por otro lado, caracterizar tumores de mama a nivel metabólico combinando datos de metabolómica y proteómica con un modelo computacional del metabolismo. Las líneas celulares de cáncer de mama mostraron una respuesta heterogénea al tratamiento con metformina y rapamicina, provocando en algunos casos un arresto del ciclo celular. Polimorfismos en el gen SLC22A1 podrían ser la causa de la sensibilidad a metformina mostrada por las células MDAMB468. Además, el análisis proteómico sugiere que los tratamientos provocan alteraciones de procesos como la transcripción. El modelo computacional del metabolismo predice que el tratamiento con metformina produce una disminución en la proliferación y una activación de enzimas relacionadas con estrés oxidativo, que se validó experimentalmente. Se propone además el método de las actividades de los flujos para comparar patrones de flujos entre condiciones. En cuanto a la caracterización del metabolismo tumoral, las predicciones del modelo computacional del metabolismo son comparables al conocimiento clínico previo, y confirman la naturaleza más proliferativa de los tumores triples negativos y TN-like. Asimismo, es posible asociar las actividades de los flujos con el pronóstico. La estructura funcional, que ya había sido vista en los modelos gráficos probabilísticos basados en expresión génica y proteómica, se mantiene con los datos de metabolómica. El análisis combinado de los datos de expresión génica y metabolómica permitió establecer relaciones entre genes y metabolitos. Combinando las actividades de los flujos con datos de metabolómica se observó coherencia funcional entre metabolitos y la actividad de flujo asociada. En este trabajo, se emplearon modelos computacionales junto a datos ómicos para caracterizar en líneas celulares la respuesta a fármacos que afectan al metabolismo y las diferencias a nivel metabólico entre tumores de cáncer de mama. Además se propone un nuevo método para comparar patrones de flujo que ha demostrado su utilidad para caracterizar respuesta a fármacos y proponer nuevos factores con valor pronóstico. Finalmente, se creó una interfaz para llevar a cabo los análisis con el modelo computacional del metabolismo sin necesidad de conocimientos de programación.Reprogramming of metabolism is a hallmark of cancer. It is described that breast cancer subtypes present differences in metabolic processes, being drugs targeting metabolism good candidates for treatment of this disease. The aim of this work is, on the one hand, the characterization of the response against two drugs targeting metabolism (metformin and rapamycin) and, on the other hand, the characterization of breast tumors at a metabolic level using metabolomics and proteomics data and computational metabolic models. Breast cancer cell lines showed a heterogeneous response against metformin and rapamycin, causing a cell cycle disruption. Polymorphisms in SLC22A1 may be the reason of the sensibility of MDAMB468 to metformin. On the other hand, proteomics analyses suggest differences in functional processes, such as transcription, due to the treatments. Moreover, the metabolic computational model predicts a decrease in growth and an activation of enzymes related with oxidative stress (experimentally validated) caused by metformin. A method to compare flux patterns named flux activities was also proposed. Predictions from computational metabolic models are comparable with previous clinical knowledge, being more proliferative triple negative and TN-like tumors. It was also possible to associate flux activities with prognosis. Strikingly, the functional structure showed in probabilistic graphical models from gene or protein expression data is remained in metabolomics. Combining gene expression and metabolomics data, it was possible to establish relationships between genes and metabolites. Combining flux activities and metabolomics data coherence was showed between metabolites and the associated flux activity. In this work, computational models, proteomics, metabolomics and gene expression data were employed to characterize response against drugs targeting metabolism in cell lines and metabolic differences between breast tumors. Additionally, a new method to compare flux patterns was proposed and it has demonstrated its utility in the characterization of response and its association with prognosis. Finally, the creation of an interface allows the management of computational metabolic models. Lastly, an interface was created in order to manage metabolic computational models without the necessity to know programming

Comprehensive Characterization of the Mutational Landscape in Localized Anal Squamous Cell Carcinoma

Carcinoma anal de cèl·lules escamoses; Neoplàsia rara; PronòsticCarcinoma anal de células escamosas; Neoplasia rara; PronósticoAnal squamous cell carcinoma; Rare neoplasm; PrognosisAnal squamous cell carcinoma (ASCC) is a rare neoplasm. Chemoradiotherapy is the standard of care, with no therapeutic advances achieved over the past three decades. Thus, a deeper molecular characterization of this disease is still necessary. We analyzed 46 paraffin-embedded tumor samples from patients diagnosed with primary ASCC by exome sequencing. A bioinformatics approach focused in the identification of high-impact genetic variants, which may act as drivers of oncogenesis, was performed. The relation between genetics variants and prognosis was also studied. The list of high-impact genetic variants was unique for each patient. However, the pathways in which these genes are involved are well-known hallmarks of cancer, such as angiogenesis or immune pathways. Additionally, we determined that genetic variants in BRCA2 , ZNF750 , FAM208B , ZNF599 , and ZC3H13 genes are related with poor disease-free survival in ASCC. This may help to stratify the patient's prognosis and open new avenues for potential therapeutic intervention. In conclusion, sequencing of ASCC clinical samples appears an encouraging tool for the molecular portrait of this disease.This study was supported by Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry , Spain and co-funded by the FEDER program “Una forma de hacer Europa” ( PI15/01310 ), a Roche Farma funding, Amgen and a grant from Grupo Español Multidisciplinar en Cáncer Digestivo ( GEMCAD1403 ). L. T.-F. is supported by the Spanish Economy and Competitiveness Ministry ( DI-15-07614 ). G. P.-V. and E. L.-C. are supported by the Consejería de Educación, Juventud y Deporte of Comunidad de Madrid ( IND2017/BMD7783 ); A. Z.-M. is supported by a Jesús Antolín Garciarena fellowship from IdiPAZ . The funders played no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript

Description of the genetic variants identified in a cohort of patients diagnosed with localized anal squamous cell carcinoma and treated with panitumumab

Càncer; Genètica mèdica; Marcadors predictiusCáncer; Genética Médica; Marcadores predictivosCancer; Medical genetics; Predictive markersSquamous cell carcinoma is the most frequent histologic type of anal carcinoma. The standard of care since the 1970s has been a combination of 5-fluorouracil, mitomycin C, and radiotherapy. This treatment is very effective in T1/T2 tumors (achieving complete regression in 80–90% of tumors). However, in T3/T4 tumors, the 3-year relapse free survival rate is only 50%. The VITAL trial aimed to assess the efficacy and safety of panitumumab in combination with this standard treatment. In this study, 27 paraffin-embedded samples from the VITAL trial and 18 samples from patients from daily clinical practice were analyzed by whole-exome sequencing and the influence of the presence of genetic variants in the response to panitumumab was studied. Having a moderate- or high-impact genetic variant in PIK3CA seemed to be related to the response to panitumumab. Furthermore, copy number variants in FGFR3, GRB2 and JAK1 were also related to the response to panitumumab. These genetic alterations have also been studied in the cohort of patients from daily clinical practice (not treated with panitumumab) and they did not have a predictive value. Therefore, in this study, a collection of genetic alterations related to the response with panitumumab was described. These results could be useful for patient stratification in new anti-EGFR clinical trials.LT-F is supported by the Spanish Economy and Competitiveness Ministry (DI-15-07614)

Isotopologue multipoint calibration for proteomics biomarker quantification in clinical practice

Targeted proteomics has become the method of choice for biomarker validation in human biopsies due to its high sensitivity, reproducibility, accuracy, and precision. However, for targeted proteomics to be transferred to clinical routine there is the need to reduce its complexity, make its procedures simpler, increase its throughput, and improve its analytical performance. Here we present the Isotopologue Multipoint Calibration (ImCal) quantification strategy, which uses a mix of isotopologue peptides to generate internal multipoint calibration curves for each individual sample and to accurately quantify biomarker peptides in clinical applications without the need of expert supervision. ImCal relies on the use of five different isotopically-labelled peptides of different nominal mass mixed at different concentrations to be used as an internal calibration curve for each endogenous peptide. The use of internal multipoint calibration curves is well-suited for the generation of ready-to-use biomarker kits for clinical applications as it is compatible with both high- and low-resolution mass spectrometers and different levels of endogenous peptide, it eliminates the need for blank matrixes required in external curves, it allows the evaluation of matrix effects and the valid quantification range in each individual sample, and it does not require expert adjustment. We used the ImCal method to quantify HER2 in 35 breast cancer formalin-fixed paraffin-embedded patient samples, revealing a high degree of heterogeneity among patients, which contrasts with the homogeneous immunohistochemistry patient classification. Our work illustrates how an improvement of mass spectrometry methods for biomarker quantification can provide fine-grain patient stratification, and thus better disease diagnostic and prognosis.The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by Grant PT17/0019/0021 of the PE I+D+i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science, Innovation and Universities, “Centro de Excelencia Severo Ochoa 2013–2017”, Grant SEV-2012-0208, and “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” Grant (2017SGR595). This project has also received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 823839 (EPIC-XS). L.T.-F. is supported by Spanish Economy and Competitiveness Ministry (Grant DI-15-07614). The Molecular Oncology and Pathology Lab is supported by Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry, Spain, and cofunded by the FEDER program, “Una forma de hacer Europa” (Grant PI15/01310)

Genetic profile and functional proteomics of anal squamous cell carcinoma: proposal for a molecular classification

Carcinoma anal de cèl·lules escamoses; Biologia molecular; ProteòmicaAnal squamous cell carcinoma; Molecular biology; ProteomicsCarcinoma anal de células escamosas; Biología molecular; ProteómicaAnal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed. High-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groups de novo. Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level. A molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The functional analysis by the probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such as ATM, SLFN11 and DST. Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy.This study was supported by the Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry, Spain and co-sponsored by the FEDER program, “Una forma de hacer Europa” (PI15/01310), a Roche Farma grant, Cátedra UAM-Amgen and a grant of Grupo Español Multidisciplinar en Cáncer Digestivo (GEMCAD1403). LT-F is supported by the Spanish Economy and Competitiveness Ministry (DI-15–07614). GP-V is supported by the Consejería de Educación, Juventud y Deporte of Comunidad de Madrid (IND2017/BMD7783); AZ-M is supported by Jesús Antolín Garciarena fellowship from IdiPAZ. The authors have declared a conflict of interest. JAFV and AG-P are shareholders in Biomedica Molecular Medicine SL. LT-F and GP-V are employees of Biomedica Molecular Medicine SL. JC has received honoraria for scientific consulting (as speaker and advisory roles) from Novartis, Pfizer, Ipsen, Exelixis, Bayer, Eisai, Advanced Accelerator Applications, Amgen, Sanofi and Merck Serono and research support from Eisai, Novartis, Ipsen, Astrazeneca, Pfizer and Advanced Accelerator Applications. IG has received honoraria and/or travel expenses from Roche, Sanofi, Merck, Servier, Amgen and Sirtflex, and for advisory role from Merck and Sanofi. JF has received consulting and advisory honoraria from Amgen, Ipsen, Eissai, Merck, Roche and Novartis; research funding from Merck, and travel and accommodation expenses from Amgen and Servier. The other authors declare no conflicts of interest

Isotopologue multipoint calibration for proteomics biomarker quantification in clinical practice

Targeted proteomics has become the method of choice for biomarker validation in human biopsies due to its high sensitivity, reproducibility, accuracy, and precision. However, for targeted proteomics to be transferred to clinical routine there is the need to reduce its complexity, make its procedures simpler, increase its throughput, and improve its analytical performance. Here we present the Isotopologue Multipoint Calibration (ImCal) quantification strategy, which uses a mix of isotopologue peptides to generate internal multipoint calibration curves for each individual sample and to accurately quantify biomarker peptides in clinical applications without the need of expert supervision. ImCal relies on the use of five different isotopically-labelled peptides of different nominal mass mixed at different concentrations to be used as an internal calibration curve for each endogenous peptide. The use of internal multipoint calibration curves is well-suited for the generation of ready-to-use biomarker kits for clinical applications as it is compatible with both high- and low-resolution mass spectrometers and different levels of endogenous peptide, it eliminates the need for blank matrixes required in external curves, it allows the evaluation of matrix effects and the valid quantification range in each individual sample, and it does not require expert adjustment. We used the ImCal method to quantify HER2 in 35 breast cancer formalin-fixed paraffin-embedded patient samples, revealing a high degree of heterogeneity among patients, which contrasts with the homogeneous immunohistochemistry patient classification. Our work illustrates how an improvement of mass spectrometry methods for biomarker quantification can provide fine-grain patient stratification, and thus better disease diagnostic and prognosis.The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by Grant PT17/0019/0021 of the PE I+D+i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science, Innovation and Universities, “Centro de Excelencia Severo Ochoa 2013–2017”, Grant SEV-2012-0208, and “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” Grant (2017SGR595). This project has also received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 823839 (EPIC-XS). L.T.-F. is supported by Spanish Economy and Competitiveness Ministry (Grant DI-15-07614). The Molecular Oncology and Pathology Lab is supported by Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry, Spain, and cofunded by the FEDER program, “Una forma de hacer Europa” (Grant PI15/01310)