Cost-effectiveness of precision medicine in gastrointestinal stromal tumor and gastric adenocarcinoma

Zeichner, Simon B.; Goldstein, Daniel A.; Kohn, Christine G.; Flowers, Christopher R.

doi:10.21037/jgo.2016.04.03

Cited by 13 publications

(10 citation statements)

References 63 publications

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“…Interestingly, genomic and proteomic biomarkers are being used to determine the appropriate treatment options for each patient, and health experts are using the best information management tools to access and share patient pathological data to develop targeted therapies. However, there has been slow progress in immaculately calculating the cost of precision medicine [ 138 ]. Further, due to advances in proteogenomic and pharmacogenomics technologies, personalized cancer care has immense opportunity to lower the cost of cancer treatment [ 138 , 139 ].…”

Section: The Cost Effectiveness Of Precision Medicine In a Health mentioning

confidence: 99%

“…However, there has been slow progress in immaculately calculating the cost of precision medicine [ 138 ]. Further, due to advances in proteogenomic and pharmacogenomics technologies, personalized cancer care has immense opportunity to lower the cost of cancer treatment [ 138 , 139 ]. Interestingly, the novelty for personalized medicine is the prospect of introducing a new personalized health care model in patient care.…”

Section: The Cost Effectiveness Of Precision Medicine In a Health mentioning

confidence: 99%

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Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

Shukla

2017

Proteomes

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During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein–protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

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Section: The Cost Effectiveness Of Precision Medicine In a Health mentioning

confidence: 99%

Section: The Cost Effectiveness Of Precision Medicine In a Health mentioning

confidence: 99%

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

Shukla

2017

Proteomes

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“…It is the fourth most common cancer with ∼1 million new cases annually and is the third leading cause of cancer-associated death globally (1,2). The reasons for its associated high mortality include its innate aggressiveness and the fact that it is often only detected once it has become advanced, with ∼60% of patients having disease that is locally or systemically advanced upon diagnosis (3). Despite recent development of diagnostic and therapeutic methods, the 5-years overall survival (OS) of the disease remains poor and ranges from 10 to 30% (4,5).…”

Section: Introductionmentioning

confidence: 99%

“…It is a relatively rare tumor type, but can be readily cured in many cases, with patients having 5-years OS rates of 60-85% (6). Indeed, the prognosis for GST patients with advanced disease has improved significantly in recent years, whereas similar gains have not been made with respect to GC (3,7). The orally administered tyrosine kinase inhibitor imatinib is one of the key mediators of these survival gains in GST patients (8,9); the identification of novel c-KIT mutations and the combination of imatinib with other therapeutic agents have helped to further treat those affected by GST (10).…”

Section: Introductionmentioning

confidence: 99%

Difference in Perfusion Parameters Between Gastric Cancer and Gastric Stromal Tumors: Evaluation With Oral Contrast Plus Contrast-Enhanced Ultrasonography

Wang

Kou

et al. 2020

Front. Oncol.

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Objective: To explore the difference of perfusion parameters between gastric cancer (GC) and gastric stromal tumors (GSTs) by using oral contrast plus contrast-enhanced ultrasonography (OC+CEUS). Methods: We retrospectively reviewed 149 patients with histologically confirmed gastric lesions (80 patients with GC and 69 patients with GST). OC+CEUS was performed in all patients in the GC group and the GST group before surgery. The cine loops of OC+CEUS of all cases were analyzed. The perfusion parameters including arrival time (AT), time to peak (TTP), basal intensity (BI), and peak intensity (PI) were obtained via a program designed for autotracking contrast quantification (ACQ). The between-group differences in these parameters were compared. Results: According to time-intensity curve (TIC) analysis, high-risk GST had higher PI than low-risk GST (P < 0.05). GC had faster AT and higher PI than normal gastric wall (P < 0.05); GST had higher PI than normal gastric wall (P < 0.05). Furthermore, the GC group had faster AT and higher PI than the GST group (P < 0.05). In contrast, the difference in BI and peak time (TTP) between the groups was not significant (P > 0.05). Conclusion: AT and PI differ significantly between the GC group and the GST group. As a new method, OC+CEUS has value for the differential diagnosis of GC and GST.

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“…The late diagnosis can signi cantly effect on the 5-year survival rate. In the past decade, due to the advancement of therapeutic treatment and medicine, the prognosis has improved, but it is still not satis ed for the disease-free survival time (3). Thus, it is challenging and necessary to understand the underlying mechanisms of GC occurrence and progression and develop novel biomarker or treatment target.…”

Section: Introductionmentioning

confidence: 99%

Identification of lncRNA-associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

Jin

2020

Preprint

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Background: Gastric cancer (GC) is one of the common digestive malignancies worldwide and causes a severe public health issue. So far, the underlying mechanisms of GC are largely unclear. Thus, our aim is to identify the long non-coding RNA (lncRNA) associated competing endogenous RNA (ceRNA) specialized for occurrence and progression in GC.Methods: The comprehensive online dataset, TCGA, was downloaded and used for identification of differentially expressed (DE) lncRNA, miRNA and mRNA screen with the value of logFC = 1 and FDR < 0.05, respectively. The interactions between lncRNA and miRNA as well mRNA and miRNA were predicted via multiple online databases, such as miRcode and Targetscan. Then the ceRNA network was constructed accompanied with gene set enrichment analysis and survival analysis. In addition, RT-qPCR and in vitro assay was carried out to validate the effect of the hub lncRNAs.Results: We identified 1485 lncRNAs, 312 miRNAs and 4260 mRNAs were differentially expressed between GC and normal tissues, respectively. Then, we generated a ceRNA network with 909 edges and 253 nodes including 76 lncRNA, 18 miRNA and 159 mRNA. This ceRNA network was involved in MET activates PTK2 signalling, MET promotes cell motility and non-integrin membrane-ECM interactions. Next, by univariate and multivariate analysis, there were 9 hub lncRNAs emerged and were associated subnetwork involved in actin filament binding and MAPK signaling pathway. The in vitro assay indicated lncRNA INHBA-AS1 and CCDC144NL-AS1 may positively related to the GC aggressive features, including proliferation, invasion and migration.Conclusion: In summary, we constructed a ceRNA network involved in the GC development. Moreover, we also identified 9 hub lncRNA-associated network related to prognosis of GC and validated two out of them as promising oncogenes. This may provide potential biomarkers or therapeutic target for GC in future.

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Cost-effectiveness of precision medicine in gastrointestinal stromal tumor and gastric adenocarcinoma

Cited by 13 publications

References 63 publications

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

Difference in Perfusion Parameters Between Gastric Cancer and Gastric Stromal Tumors: Evaluation With Oral Contrast Plus Contrast-Enhanced Ultrasonography

Identification of lncRNA-associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

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