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Background and objectives: Dimensional response is an unmet need in second lines of advanced soft tissue sarcomas (STS). Indeed, the three approved drugs, pazopanib, trabectedin, and eribulin, achieved an overall response rate (ORR) of less than 10%. This fact potentially hinders the options for fast symptomatic relief or surgical rescue. The combination of trabectedin plus low-dose radiation therapy (T-XRT) demonstrated a response rate of 60% in phase I/II trial, while real-life data achieved 32.5% ORR, probably due to a more relaxed timing between treatments. These results were obtained in progressing and advanced STS. In this study, the merged databases (trial plus real life) have been analyzed, with a special focus on leiomyosarcoma patients. Design and methods: As responses were seen in a wide range of sarcoma histologies (11), this study planned to analyze whether leiomyosarcoma, the largest subtype with 26 cases (30.6%) in this series, exhibited a better clinical outcome with this therapeutic strategy. In addition, four advanced and progressing leiomyosarcoma patients, all with extraordinarily long progression-free survival of over 18 months, were collected. Results: A total of 847 cycles of trabectedin were administered to 85 patients, with the median number of cycles per patient being 7 (1-45+). A trend toward a longer progression-free survival (PFS) was observed in leiomyosarcoma patients with median PFS (mPFS) of 9.9 months [95% confidence interval (CI): 1.1-18.7] versus 5.6 months (95% CI: 3.2-7.9) for the remaining histologies, p = 0.25. When leiomyosarcoma and liposarcoma were grouped, this difference reached statistical significance, probably due to the special sensitivity of myxoid liposarcoma. The mPFS for L-sarcomas was 12.7 months (95% CI: 7-18.5) versus 4.3 months (95% CI: 3.3-5.3) for the remaining histologies, p = 0.001. Cases with long-lasting disease control are detected among leiomyosarcoma patients. Conclusion: Even when extraordinarily long-lasting responses do exist among leiomyosarcoma patients treated with T-XR, we were unable to demonstrate a significant difference favoring leiomyosarcoma patients in clinical outcomes.
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Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide, generating huge economic and social impacts that have not slowed in recent years. Oncological treatment for this neoplasm usually includes surgery, chemotherapy, treatments on molecular targets and ionizing radiation. The prognosis in terms of overall survival (OS) and the different therapeutic responses between patients can be explained, to a large extent, by the existence of widely heterogeneous molecular profiles. The identification of prognostic and predictive gene signatures of response to cancer treatment, could help in making therapeutic decisions in patients affected by NSCLC. Given the published scientific evidence, we believe that the search for prognostic and/or predictive gene signatures of response to radiotherapy treatment can significantly help clinical decision-making. These signatures may condition the fractions, the total dose to be administered and/or the combination of systemic treatments in conjunction with radiation. The ultimate goal is to achieve better clinical results, minimizing the adverse effects associated with current cancer therapies.
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Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death worldwide, generating an enormous economic and social impact that has not stopped growing in recent years. Cancer treatment for this neoplasm usually includes surgery, chemotherapy, molecular targeted treatments, and ionizing radiation. The prognosis in terms of overall survival (OS) and the disparate therapeutic responses among patients can be explained, to a great extent, by the existence of widely heterogeneous molecular profiles. The main objective of this study was to identify prognostic and predictive gene signatures of response to cancer treatment involving radiotherapy, which could help in making therapeutic decisions in patients with NSCLC. To achieve this, we took as a reference the differential gene expression pattern among commercial cell lines, differentiated by their response profile to ionizing radiation (radiosensitive versus radioresistant lines), and extrapolated these results to a cohort of 107 patients with NSCLC who had received radiotherapy (among other therapies). We obtained a six-gene signature (APOBEC3B, GOLM1, FAM117A, KCNQ1OT1, PCDHB2, and USP43) with the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received. Patients who had an unfavorable prognostic signature had a median OS of 24.13 months versus 71.47 months for those with a favorable signature, and the median PFS was 12.65 months versus 47.11 months, respectively. We also carried out a univariate analysis of multiple clinical and pathological variables and a bivariate analysis by Cox regression without any factors that substantially modified the HR value of the proposed gene signature.
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Colorectal cancer (CRC) is the third most common cancer worldwide. The standard treatment in locally advanced rectal cancer is preoperative radiation alone or in combination with chemotherapy, followed by adjuvant chemotherapy. Rectal cancer is highly lethal, with only 20% of patients showing a complete remission (by RECIST) after standard treatment, although they commonly show local or systemic relapse likely due to its late detection and high chemotherapy resistance, among other reasons. Here, we explored the role of PAI1 (Serpin E1) in rectal cancer through the analyses of public patient databases, our own cohort of locally advanced rectal cancer patients and a panel of CRC cell lines. We showed that PAI1 expression is upregulated in rectal tumors, which is associated with decreased overall survival and increased metastasis and invasion in advanced rectal tumors. Accordingly, PAI1 expression is correlated with the expression of (Epithelial-to-Mesenchymal Transition) EMT-associated genes and genes encoding drug targets, including the tyrosine kinases PDGFRb, PDGFRa and FYN, the serine/threonine kinase PIM1 and BRAF. In addition, we demonstrate that cells expressing PAI1 protein are more sensitive to the PIM inhibitor AZD1208, suggesting that PAI1 could be used to predict response to treatment with PIM inhibitors and to complement radiotherapy in rectal tumors.
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Inibidor 1 de Ativador de Plasminogênio/metabolismo , Neoplasias Retais/metabolismo , Adulto , Idoso , Apoptose/efeitos dos fármacos , Biomarcadores Farmacológicos , Biomarcadores Tumorais , Compostos de Bifenilo/farmacologia , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/metabolismo , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/tratamento farmacológico , Recidiva Local de Neoplasia/metabolismo , Inibidor 1 de Ativador de Plasminogênio/fisiologia , Prognóstico , Inibidores de Proteínas Quinases , Proteínas Serina-Treonina Quinases/metabolismo , Neoplasias Retais/tratamento farmacológico , Tiazolidinas/farmacologiaRESUMO
Importance: Active therapeutic combinations, such as trabectedin and radiotherapy, offer potentially higher dimensional response in second-line treatment of advanced soft-tissue sarcomas. Dimensional response can be relevant both for symptom relief and for survival. Objective: To assess the combined use of trabectedin and radiotherapy in treating patients with progressing metastatic soft-tissue sarcomas. Design, Setting, and Participants: Phase 1 of this nonrandomized clinical trial followed the classic 3 + 3 design, with planned radiotherapy at a fixed dose of 30 Gy (3 Gy/d for 10 days) and infusion of trabectedin at 1.3 mg/m2 as the starting dose, 1.5 mg/m2 as dose level +1, and 1.1 mg/m2 as dose level -1. Phase 2 followed the Simon optimal 2-stage design. Allowing for type I and II errors of 10%, treatment success was defined as an overall response rate of 35%. This study was conducted in 9 sarcoma referral centers in Spain, France, and Italy from April 13, 2015, to November 20, 2018. Adult patients with progressing metastatic soft-tissue sarcoma and having undergone at least 1 previous line of systemic therapy were enrolled. In phase 2, patients fitting inclusion criteria and receiving at least 1 cycle of trabectedin and the radiotherapy regimen constituted the per-protocol population; those receiving at least 1 cycle of trabectedin, the safety population. Interventions: Trabectedin was administered every 3 weeks in a 24-hour infusion. Radiotherapy was required to start within 1 hour after completion of the first trabectedin infusion (cycle 1, day 2). Main Outcomes and Measures: The dose-limiting toxic effects of trabectedin (phase 1) and the overall response rate (phase 2) with use of trabectedin plus irradiation in metastatic soft-tissue sarcomas. Results: Eighteen patients (11 of whom were male) were enrolled in phase 1, and 27 other patients (14 of whom were female) were enrolled in phase 2. The median ages of those enrolled in phases 1 and 2 were 42 (range, 23-74) years and 51 (range, 27-73) years, respectively. In phase 1, dose-limiting toxic effects included grade 4 neutropenia lasting more than 5 days in 1 patient at the starting dose level and a grade 4 alanine aminotransferase level increase in 1 of 6 patients at the +1 dose level. In phase 2, among 25 patients with evaluable data, the overall response rate was 72% (95% CI, 53%-91%) for local assessment and 60% (95% CI, 39%-81%) for central assessment. Conclusions and Relevance: The findings of this study suggest that the recommended dose of trabectedin for use in combination with this irradiation regimen is 1.5 mg/m2. The trial met its primary end point, with a high overall response rate that indicates the potential of this combination therapy for achieving substantial tumor shrinkage beyond first-line systemic therapy in patients with metastatic, progressing soft-tissue sarcomas. Trial Registration: ClinicalTrials.gov Identifier: NCT02275286.
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Sarcoma/tratamento farmacológico , Sarcoma/radioterapia , Trabectedina/administração & dosagem , Adulto , Idoso , Terapia Combinada , Intervalo Livre de Doença , Relação Dose-Resposta a Droga , Relação Dose-Resposta à Radiação , Feminino , França/epidemiologia , Humanos , Itália/epidemiologia , Masculino , Pessoa de Meia-Idade , Metástase Neoplásica , Sarcoma/patologia , Espanha/epidemiologia , Trabectedina/efeitos adversosRESUMO
Rectal cancer represents approximately 10% of cancers worldwide. Preoperative chemoradiotherapy increases complete pathologic response and local control, although it offers a poor advantage in survivorship and sphincter saving compared with that of radiotherapy alone. After preoperative chemoradiotherapy, approximately 20% of patients with rectal cancer achieve a pathologic complete response to the removed surgical specimen; this response may be related to a better prognosis and an improvement in disease-free survival. However, better biomarkers to predict response and new targets are needed to stratify patients and obtain better response rates. MAP17 (PDZK1IP1) is a small, 17 kDa non-glycosylated membrane protein located in the plasma membrane and Golgi apparatus and is overexpressed in a wide variety of human carcinomas. MAP17 has been proposed as a predictive biomarker for reactive oxygen species, ROS, inducing treatments in cervical tumors or laryngeal carcinoma. Due to the increase in ROS, MAP17 is also associated with the marker of DNA damage, phosphoH2AX (pH2AX). In the present manuscript, we examined the values of MAP17 and pH2AX as surrogate biomarkers of the response in rectal tumors. MAP17 expression after preoperative chemoradiotherapy is able to predict the response to chemoradiotherapy, similar to the increase in pH2AX. Furthermore, we explored whether we can identify molecular targeted therapies that could help improve the response of these tumors to radiotherapy. In this sense, we found that the inhibition of DNA damage with olaparib increased the response to radio- and chemotherapy, specifically in tumors with high levels of pH2AX and MAP17.
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Gliomas are the most prevalent primary malignant brain tumors associated with poor prognosis. NAMPT, a rate-limiting enzyme that boosts the nicotinamide adenine dinucleotide (NAD) regeneration in the salvage pathway, is commonly expressed in these tumors. NAD metabolism is required to maintain tissue homeostasis. To maintain metabolism, cancer cells require a stable NAD regeneration circuit. However, high levels of NAD confer resistance to therapy to these tumors, usually treated with Temozolomide (TMZ). We report that NAMPT overexpression in glioma cell lines increases tumorigenic properties controlling stem cell pathways and enriching the cancer-initiating cell (CIC) population. Furthermore, NAMPT expression correlated with high levels of Nanog, CD133 and CIC-like cells in glioblastoma directly extracted from patients. Meta-analysis reveals that NAMPT is also a key factor inducing cancer stem pathways in glioma cells. Furthermore, we report a novel NAMPT-driven signature which stratify prognosis within tumor staging. NAMPT signature also correlates directly with EGFR positive and IDH negative tumors. Finally, NAMPT inhibition increases sensitivity to apoptosis in both NAMPT-expressing cells and tumorspheres. Therefore, NAMPT represents a novel therapeutic target in Glioma progression and relapse.
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Sarcomas are malignant tumors accounting for a high percentage of cancer morbidity and mortality in children and young adults. Surgery and radiation therapy are the accepted treatments for most sarcomas; however, patients with metastatic disease are treated with systemic chemotherapy. Many tumors display marginal levels of chemoresponsiveness, and new treatment approaches are needed. MAP17 is a small non-glycosylated membrane protein overexpressed in carcinomas. The levels of MAP17 could be used as a prognostic marker to predict the response to bortezomib in hematological malignancies and in breast tumors. Therefore, we analyzed the expression of this oncogene in sarcomas and its relationship with clinico-pathological features, as well as tested whether it can be used as a new biomarker to predict the therapeutic response to bortezomib and new therapies for sarcomas. We found that the levels of MAP17 were related to clinical features and poor survival in a cohort of 69 patients with different sarcoma types, not being restricted to any special subtype of tumor. MAP17 expression is associated with poor overall survival (p<0.001) and worse disease-free survival (p=0.002). Cell lines with high levels of MAP17 show a better response to bortezomib in vitro. Furthermore, patient-derived xenografts (PDX) with high levels of MAP17 respond to bortezomib in vivo. Our results showed that this response is due to the lower levels of NFκB and autophagy activation. Therefore, we suggest that MAP17 is a new biomarker to predict the efficacy of bortezomib as a new therapy for sarcomas.
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Antineoplásicos/uso terapêutico , Biomarcadores Tumorais/análise , Bortezomib/uso terapêutico , Proteínas de Membrana/biossíntese , Adolescente , Adulto , Idoso , Animais , Área Sob a Curva , Intervalo Livre de Doença , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Camundongos , Pessoa de Meia-Idade , Prognóstico , Curva ROC , Sarcoma/tratamento farmacológico , Sarcoma/metabolismo , Sensibilidade e Especificidade , Ensaios Antitumorais Modelo de Xenoenxerto , Adulto JovemRESUMO
Objetivo. El estadio del cáncer de mama constituye uno de los factores pronósticos más relevantes. Sin embargo, la compleja clasificación TNM, la existencia de diferentes versiones y la variabilidad de la fuente de la información hacen que la recogida de datos sobre texto libre sea compleja. El objetivo de este trabajo es desarrollar una herramienta que permita ayudar a la estadificación de manera automática. Pacientes y métodos. El trabajo incluyó el estudio de los informes de 100 pacientes con cáncer de mama no metastásico tratadas con cirugía y radioterapia en 2012. La recogida del tamaño tumoral posquirúrgico (séptima edición TNM) se realizó con la herramienta desarrollada y manualmente por un médico en formación especializada de tercer año de oncología radioterápica. Resultados. La aplicación fue capaz de detectar el 62% de los casos tras examinar los informes de anatomía patológica, y el 77% al añadir el examen de los informes de oncología radioterápica. Los casos no detectados se debieron a que la información estaba almacenada en otra sección de la estación clínica. Comparando los resultados entre la aplicación y la recogida manual, hubo una diferencia del 13% (10/77). Se observó que en el 50% de los casos (5/10) la aplicación era correcta, mientras que en el otro 50% lo fue la recogida manual. Conclusiones. Esta herramienta innovadora permite recoger automáticamente el tamaño tumoral en el cáncer de mama, ahorrando tiempo en la recogida de datos y evitando errores en la clasificación tumoral, por lo que puede contribuir de modo notable en la decisión terapéutica(AU)
Objective. Staging of breast cancer is one of the most important prognostic factors. However, collecting data for staging manually from unstructured free text is variable and imprecise because of the complexity of the TNM classification, the existence of different versions over time, and variability in the source used to obtain data. The aim of this study was to develop an artificial intelligence tool to allow data on tumoral staging to be mined automatically. Patients and methods. The study included the reports of the first 100 patients with nonmetastatic breast cancer treated with surgery and radiotherapy in 2012. Data on postoperative tumor size (TNM seventh edition) were collected with a specially designed software tool and manually by a third-year resident physician in radiation oncology. Results. The software application detected 62% of cases when pathology reports were included, and 77% when radiation oncology reports were added. Non-detection was due to the information being stored in another section of the clinical station. When we compared the results of the software application and manual collection, we found a difference of 13% (10/77). In these 10 cases, the application was correct in 50%, while manual collection was correct in the remaining 50%. Conclusions. This innovative system allows automatic staging of tumoral size in breast cancer. The use of this tool would save time in data collection and prevent errors in tumoral classification and could also improve therapeutic decisions(AU)