Novel Biomarkers for Prediction of Response to Preoperative Systemic Therapies in Gastric Cancer.
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ABSTRACT:
SUBMITTER: Cavaliere A
PROVIDER: S-EPMC6928085 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
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Project description:Gastric cancer (GC) is the second leading cause of cancer mortality and the fourth most commonly diagnosed malignant diseases. While continued efforts have been focused on GC treatment, the introduction of trastuzumab marked the beginning of a new era of target-specific treatments. Considering the diversity of mutations in GC, satisfactory results obtained from various target-specific therapies were expected, yet most of them were unsuccessful in controlled clinical trials. There are several possible reasons underlying the failures, including the absence of patient selection depending on validated predictive biomarkers, the inappropriate combination of drugs, and tumor heterogeneity. In contrast to targeted agents, immuno-oncologic agents are designed to regulate and boost immunity, are not target-specific, and may overcome tumor heterogeneity. With the successful establishment of predictive biomarkers, including Epstein-Barr virus pattern, microsatellite instability status, and programmed death-ligand 1 (PD-L1) expression, as well as ideal combination regimens, a new frontier in the immuno-oncology of GC treatment is on the horizon. Since the field of immuno-oncology has witnessed innovative, practice-changing successes in other cancer types, several trials on GC are ongoing. Among immuno-oncologic therapies, immune checkpoint inhibitors are the mainstay of clinical trials performed on GC. In this article, we review target-specific agents currently used in clinics or are undergoing clinical trials, and highlight the future clinical application of immuno-oncologic agents in inoperable GC.
| S-EPMC5881006 | biostudies-literature
Project description:Background: Carcinoembryonic antigen (CEA) is one of the important indexes for the diagnosis and prognosis of gastrointestinal cancer. Systemic inflammatory response (SIR) is closely related to the occurrence and development of gastrointestinal cancer. Methods: A total of 803 patients who underwent radical gastrectomy in Qinghai University Affiliated Hospital from January 2012 to December 2016 were included as training set. Multivariable Cox proportional hazard regression was used to identify associations with outcome of gastric cancer (GC). CNLR was established by combining CEA and the neutrophils to lymphocytes ratio (NLR, a typical parameter in SIR) to generate a novel prognostic score system and its prognostic value was externally validated. Results: Multivariate analysis showed that CEA and NLR were independent prognostic factors for GC patients (both p < 0.05). A higher CNLR was significantly associated with older age, male sex, larger tumor size, vascular invasion and advanced stages (all p < 0.05). Patients with higher CNLR had poor prognosis than those with lower CNLR (p < 0.05). Multivariate analysis showed that CNLR was an independent prognostic factor (p < 0.05). Incorporation of the CNLR into a prognostic model including age and TNM stage generated a nomogram, which predicted accurately 3- and 5-year survival for GC patients. And similar results were obtained in the external validation set. Conclusions: The CNLR prognostic scoring system established by combining CEA and NLR is an independent prognostic factor for GC, which can be incorporated into the traditional TNM staging to improve the prediction of long-term survival outcomes.
| S-EPMC7778548 | biostudies-literature
Project description:Background:Determining preferences regarding the benefits of adjuvant chemotherapy (AC) for stage I GC is critical. Methods:We retrospectively reviewed 1069 patients with pathologically confirmed stage I GC who underwent R0 gastrectomy between 2006 and 2014. Univariate and multivariate survival analyses were conducted. Systemic inflammation factors were used to develop a scoring system for predicting AC benefits. Results:With a median follow-up of 47 months (range 3-113 months), the 5-year overall survival (OS) rate was 90.5%. The patient score was 1 for either a pretreatment hypoalbuminemia or elevated derived neutrophil-lymphocyte ratio (dNLR) and was 0 otherwise. The SIS served as an independent prognostic factor for reduced OS. AC was delivered to 13.5% (144/1069) of all patients. Compared to surgery alone, AC had no significant effect on survival in both the entire cohort and the IA/IB subgroup. However, in the high-risk group (SIS?=?2), patients with AC had a significantly better OS than those undergoing surgery alone. Conclusions:Patients with SIS?=?2 may benefit from AC and thus may be considered candidates for adjuvant treatment. However, to confirm our findings, future prospective studies are warranted.
| S-EPMC6079442 | biostudies-literature
Project description:Globally, gastric cancer is the 4(th) most frequently diagnosed cancer and the 2(nd) leading cause of death from cancer, with an estimated 990000 new cases and 738000 deaths registered in 2008. In the advanced setting, standard chemotherapies protocols acquired an important role since last decades in prolong survival. Moreover, recent advances in molecular therapies provided a new interesting weapon to treat advanced gastric cancer through anti-human epidermal growth factor receptor 2 (HER2) therapies. Trastuzumab, an anti-HER2 monoclonal antibody, was the first target drug in the metastatic setting that showed benefit in overall survival when in association with platinum-5-fluorouracil based chemotherapy. Further, HER2 overexpression analysis acquired a main role in predict response for trastuzumab in this field. Thus, we conducted a review that will discuss the main points concerning trastuzumab and HER2 in gastric cancer, providing a comprehensive overview of molecular mechanisms and novel trials involved.
| S-EPMC3801309 | biostudies-literature
Project description:The last decade has witnessed significant growth in therapeutic options for patients diagnosed with lung cancer. This is due in major part to our improved technological ability to interrogate the genomics of cancer cells, which has enabled the development of biologically rational anticancer agents. The recognition that lung cancer is not a single disease entity dates back many decades to the histological subclassification of malignant neoplasms of the lung into subcategories of small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). While SCLC continues to be regarded as a single histologic and therapeutic category, the NSCLC subset has undergone additional subcategorizations with distinct management algorithms for specific histologic and molecular subtypes. The defining characteristics of these NSCLC subtypes have evolved into important tools for prognosis and for predicting the likelihood of benefit when patients are treated with anticancer agents.
| S-EPMC4637259 | biostudies-literature
Project description:BACKGROUND:Technological advances including high-throughput sequencing have identified numerous tumor-specific genetic changes in pediatric and adolescent cancers that can be exploited as targets for novel therapies. SCOPE OF REVIEW:This review provides a detailed overview of recent advances in the application of target-specific therapies for childhood cancers, either as single agents or in combination with other therapies. The review summarizes preclinical evidence on which clinical trials are based, early phase clinical trial results, and the incorporation of predictive biomarkers into clinical practice, according to cancer type. MAJOR CONCLUSIONS:There is growing evidence that molecularly targeted therapies can valuably add to the arsenal available for treating childhood cancers, particularly when used in combination with other therapies. Nonetheless the introduction of molecularly targeted agents into practice remains challenging, due to the use of unselected populations in some clinical trials, inadequate methods to evaluate efficacy, and the need for improved preclinical models to both evaluate dosing and safety of combination therapies. GENERAL SIGNIFICANCE:The increasing recognition of the heterogeneity of molecular causes of cancer favors the continued development of molecularly targeted agents, and their transfer to pediatric and adolescent populations.
| S-EPMC4633945 | biostudies-literature
Project description:ObjectiveThis study aims to differentiate preoperative Borrmann type IV gastric cancer (GC) from primary gastric lymphoma (PGL) by transfer learning radiomics nomogram (TLRN) with whole slide images of GC as source domain data.Materials and methodsThis study retrospectively enrolled 438 patients with histopathologic diagnoses of Borrmann type IV GC and PGL. They received CT examinations from three hospitals. Quantitative transfer learning features were extracted by the proposed transfer learning radiopathomic network and used to construct transfer learning radiomics signatures (TLRS). A TLRN, which integrates TLRS, clinical factors, and CT subjective findings, was developed by multivariate logistic regression. The diagnostic TLRN performance was assessed by clinical usefulness in the independent validation set.ResultsThe TLRN was built by TLRS and a high enhanced serosa sign, which showed good agreement by the calibration curve. The TLRN performance was superior to the clinical model and TLRS. Its areas under the curve (AUC) were 0.958 (95% confidence interval [CI], 0.883-0.991), 0.867 (95% CI, 0.794-0.922), and 0.921 (95% CI, 0.860-0.960) in the internal and two external validation cohorts, respectively. Decision curve analysis (DCA) showed that the TLRN was better than any other model. TLRN has potential generalization ability, as shown in the stratification analysis.ConclusionsThe proposed TLRN based on gastric WSIs may help preoperatively differentiate PGL from Borrmann type IV GC.Borrmann type IV gastric cancer, primary gastric lymphoma, transfer learning, whole slide image, deep learning.
| S-EPMC8789309 | biostudies-literature
Project description:BackgroundNovel biomarkers are required in gastric cancer (GC) treated by immunotherapy. Epstein-Barr virus (EBV) infection induces an immune-active tumor microenvironment, while its association with immunotherapy response is still controversial. Genes underlying EBV infection may determine the response heterogeneity of EBV + GC. Thus, we screened hub genes associated with EBV infection to predict the response to immunotherapy in GC.MethodsPrognostic hub genes associated with EBV infection were screened using multi-omic data of GC. EBV + GC cells were established and confirmed by EBV-encoded small RNA in situ hybridization (EBER-ISH). Immunohistochemistry (IHC) staining of the hub genes was conducted in GC samples with EBER-ISH assay. Infiltrating immune cells were stained using immunofluorescence.ResultsCHAF1A was identified as a hub gene in EBV + GC, and its expression was an independent predictor of overall survival (OS). EBV infection up-regulated CHAF1A expression which also predicted EBV infection well. CHAF1A expression also predicted microsatellite instability (MSI) and a high tumor mutation burden (TMB). The combined score (CS) of CHAF1A expression with MSI or TMB further improved prognostic stratification. CHAF1A IHC score positively correlated with the infiltration of NK cells and macrophages M1. CHAF1A expression alone could predict the immunotherapy response, but its CS with EBV infection, MSI, TMB, or PD-L1 expression showed better effects and improved response stratification based on current biomarkers.ConclusionsCHAF1A could be a novel biomarker for immunotherapy of GC, with the potential to improve the efficacy of existing biomarkers.
| S-EPMC10804498 | biostudies-literature
Project description:BackgroundPreoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients.MethodsWe used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs.ResultsBased on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833-0.999) and verification sets (AUC = 0.775, 95% CI 0.647-0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades.ConclusionsIn this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.
| S-EPMC8066490 | biostudies-literature
Project description:Continuous monitoring in the intensive care setting has transformed the capacity to rapidly respond with interventions for patients in extremis. Noninvasive monitoring has generally been limited to transdermal or intravascular systems coupled to transducers including oxygen saturation or pressure. Here it is hypothesized that gastric fluid (GF) and gases, accessible through nasogastric (NG) tubes, commonly found in intensive care settings, can provide continuous access to a broad range of biomarkers. A broad characterization of biomarkers in swine GF coupled to time-matched serum is conducted . The relationship and kinetics of GF-derived analyte level dynamics is established by correlating these to serum levels in an acute renal failure and an inducible stress model performed in swine. The ability to monitor ketone levels and an inhaled anaesthetic agent (isoflurane) in vivo is demonstrated with novel NG-compatible sensor systems in swine. Gastric access remains a main stay in the care of the critically ill patient, and here the potential is established to harness this establishes route for analyte evaluation for clinical management.
| S-EPMC8693042 | biostudies-literature