4 results on '"predicting response to therapy"'
Search Results
2. Identification of Novel Molecular Subgroups in Esophageal Adenocarcinoma to Predict Response to Neo-Adjuvant Therapies
- Author
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Sanne J. M. Hoefnagel, Willem J. Koemans, Hina N. Khan, Jan Koster, Sybren L. Meijer, Jolanda M. van Dieren, Liudmila L. Kodach, Johanna W. van Sandick, Silvia Calpe, Carmen M. del Sancho-Serra, Ana C. P. Correia, Mark I. Van Berge Henegouwen, Suzanne S. Gisbertz, Maarten C. C. M. Hulshof, Sandro Mattioli, Manon C. W. Spaander, Kausilia K. Krishnadath, Center of Experimental and Molecular Medicine, Graduate School, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Surgery, ANS - Neuroinfection & -inflammation, CCA - Cancer biology and immunology, Pathology, CCA - Imaging and biomarkers, Radiotherapy, Gastroenterology and Hepatology, and Gastroenterology & Hepatology
- Subjects
subgroups ,Cancer Research ,Oncology ,esophageal adenocarcinoma ,RNA sequencing ,predicting response to therapy ,SDG 3 - Good Health and Well-being ,Human medicine - Abstract
Simple Summary Gene expression of esophageal adenocarcinoma is highly heterogeneous. In general, these cancers have poor prognosis and unpredictable responses to chemo- and radiotherapy. Investigating expression profiles from RNA from pre-treatment biopsies are highly attractive to investigate the existence of diverse biological groups and signatures associated with the clinical response to current treatment strategies. We identified and validated three distinct biological esophageal adenocarcinoma subgroups and identified immune signatures with association to therapy response using RNA sequencing. These findings aid in understanding biological mechanisms' underlying response to neo-adjuvant treatment. Esophageal adenocarcinoma (EAC) is a highly aggressive cancer and its response to chemo- and radiotherapy is unpredictable. EACs are highly heterogeneous at the molecular level. The aim of this study was to perform gene expression analysis of EACs to identify distinct molecular subgroups and to investigate expression signatures in relation to treatment response. In this prospective observational study, RNA sequencing was performed on pre-treatment endoscopic EAC biopsies from a discovery cohort included between 2012 and 2017 in one Dutch Academic Center. Four additional cohorts were analyzed for validation purposes. Unsupervised clustering was performed on 107 patients to identify biological EAC subgroups. Specific cell signaling profiles were identified and evaluated with respect to predicting response to neo-adjuvant chemo(radio)therapy. We identified and validated three distinct biological EAC subgroups, characterized by (1) p38 MAPK/Toll-like receptor signaling; (2) activated immune system; and (3) impaired cell adhesion. Subgroup 1 was associated with poor response to chemo-radiotherapy. Moreover, an immune signature with activated T-cell signaling, and increased number of activated CD4 T memory cells, neutrophils and dendritic cells, and decreased M1 and M2 macrophages and plasma cells, was associated with complete histopathological response. This study provides a novel molecular classification for EACs. EAC subgroup 1 proved to be more therapy-resistant, while immune signaling was increased in patients with complete response to chemo-radiotherapy. Our findings give insight into the biology of EACs and in cellular signaling mechanisms underlying response to neo-adjuvant treatment. Future implementation of this classification will improve patient stratification and enhance the development of targeted therapies.
- Published
- 2022
3. Endoscopic and Clinical Variables That Predict Sustained Remission in Children With Ulcerative Colitis Treated With Infliximab.
- Author
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Turner, Dan, Griffiths, Anne M., Veerman, Gigi, Johanns, Jewel, Damaraju, Lakshmi, Blank, Marion, and Hyams, Jeffrey
- Abstract
Background & Aims: We aimed to identify early clinical, laboratory, and endoscopic factors associated with sustained remission in children with ulcerative colitis (UC) treated with infliximab. Methods: We performed a post hoc analysis of data collected from 51 children (6–17 years old) with moderate-to-severe UC treated with infliximab for 1 year in the T72 clinical trial. The primary outcome was steroid-free remission at weeks 30 and 54 of treatment, which was based on patient and physician assessments. We compared the ability of the Pediatric UC Activity Index (PUCAI, a noninvasive clinical index), levels of C-reactive protein (CRP), and mucosal healing to predict which patients would be in steroid-free sustained remission after 1 year of treatment. Results: Week 8 PUCAI scores best predicted which patients would be in steroid-free remission after 1 year of treatment; 9 of 17 patients who had PUCAI scores <10 points were in sustained remission (53%), compared with 4 of 20 who had PUCAI scores ≥10 (20%) (P = .036). Mucosal healing at week 8 was associated with steroid-free remission at 1 year, but this did not reach significance; 7 of 16 patients with mucosal healing were in remission after 1 year (44%), compared with 6 of 21 without mucosal healing (29%) (P = .34). The area under the receiver operating characteristic curve values for association with steroid-free sustained remission were 0.70 for the PUCAI (95% confidence interval [CI], 0.53–0.88), 0.56 for mucosal healing (95% CI, 0.36–0.76), and 0.44 for level of CRP (95% CI, 0.24–0.65). By using a multivariable logistic regression model, the week 8 PUCAI was the only factor associated with steroid-free remission at 1 year (P = .038). PUCAI-defined remission had a high degree of concordance with complete mucosal healing at week 8 (33% of patients were in remission according to the PUCAI vs 31% with mucosal healing). Conclusion: On the basis of a post hoc analysis of data from the T72 clinical trial on the effect of infliximab in pediatric patients with UC, the PUCAI was no less predictive of sustained remission than mucosal healing at week 8, and both were superior to CRP level. Routine endoscopic evaluation in children with UC who are in complete clinical remission (ie, PUCAI <10 points) may not be necessary. [Copyright &y& Elsevier]
- Published
- 2013
- Full Text
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4. DNA microarray-based gene expression profiling in diagnosis, assessing prognosis and predicting response to therapy in colorectal cancer
- Author
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Andrzej Kmieć, Przemyslaw Kwiatkowski, Janusz Godlewski, and Piotr M. Wierzbicki
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Adenoma ,Genetic Markers ,Microbiology (medical) ,Microarray ,Colorectal cancer ,lcsh:Medicine ,colorectal cancer ,Medical Oncology ,Bioinformatics ,assessing prognosis ,Transcriptome ,profilowanie genowe ,Humans ,Medicine ,Pathological ,Gene ,Oligonucleotide Array Sequence Analysis ,business.industry ,Gene Expression Profiling ,lcsh:R ,DNA microarray ,mikromacierze ,DNA ,Prognosis ,medicine.disease ,Gene expression profiling ,Treatment Outcome ,Infectious Diseases ,gene profiling ,Mutation ,Disease Progression ,rak jelita grubego ,Colorectal Neoplasms ,business ,predicting response to therapy - Abstract
Colorectal cancer is the most common cancer of the gastrointestinal tract. It is considered as a biological model of a certain type of cancerogenesis process in which progression from an early to late stage adenoma and cancer is accompanied by distinct genetic alterations. Clinical and pathological parameters commonly used in clinical practice are often insufficient to determine groups of patients suitable for personalized treatment. Moreover, reliable molecular markers with high prognostic value have not yet been determined. Molecular studies using DNA-based microarrays have identified numerous genes involved in cell proliferation and differentiation during the process of cancerogenesis. Assessment of the genetic profile of colorectal cancer using the microarray technique might be a useful tool in determining the groups of patients with different clinical outcomes who would benefit from additional personalized treatment. The main objective of this study was to present the current state of knowledge on the practical application of gene profiling techniques using microarrays for determining diagnosis, prognosis and response to treatment in colorectal cancer.
- Published
- 2012
- Full Text
- View/download PDF
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