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Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma.

ABSTRACT: Advanced esophago-gastric (OG) adenocarcinomas have a high mortality rate and new therapeutic options are urgently required. Despite recent advances in understanding the molecular characteristics of OG cancers, tumor heterogeneity poses a challenge in developing new therapeutics capable of improving patient outcomes. Consequently, chemotherapy remains the mainstay of systemic treatment, with the HER2 being the only predictive biomarker routinely targeted in clinical practice. Recent data indicate that immunotherapy will be incorporated into first-line chemotherapy, but further research is required to refine patient selection. This review will summarize the clinical strategies being evaluated to utilize our knowledge of predictive biomarkers with reference to novel therapeutics, and discuss the barriers to implementing precision oncology in OG adenocarcinoma.

SUBMITTER: Fong CY

PROVIDER: S-EPMC8265282 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma.

Fong Caroline Yk CY Chau Ian I

Pharmacogenomics 20210614 11

Advanced esophago-gastric (OG) adenocarcinomas have a high mortality rate and new therapeutic options are urgently required. Despite recent advances in understanding the molecular characteristics of OG cancers, tumor heterogeneity poses a challenge in developing new therapeutics capable of improving patient outcomes. Consequently, chemotherapy remains the mainstay of systemic treatment, with the HER2 being the only predictive biomarker routinely targeted in clinical practice. Recent data indicat ...[more]

PMID: 34120461

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Project description:The incidence of esophageal and junctional adenocarcinoma has increased 6-fold in the west in the last 30 years and 5 year survival remains <14%. We aimed to characterize genome-wide aberrations in esophageal adenocarcinoma to further understand disease pathogenesis and ultimately identify groups with differential survivals with implications for clinical management. Oligo-array-based high-resolution analysis of copy number changes in 89 fresh frozen esophageal adenocarcinoma resection sections with long-term clinical follow-up data was performed. Good quality array comparative genomic hybridization profiles were obtained from 56/89 of the samples (63%). Our analyses confirmed known genomic aberrations in esophageal adenocarcinoma and identified 3 novel genomic regions with copy number changes. A modified T test with adjusted Bonferroni correction identified 17 genes with significantly different log2 ratios (p<4x10-7), including 6 novel genes, that characterize a group with a poorer survival. Total RNA isolated from human tissue sections was used to make fluorescently labeled cRNA that was hybridized to DNA oligonucleotide. Briefly, 4 µg of total RNA was used to synthesize dsDNA through reverse transcription. cRNA was produced by in vitro transcription and labeled postsynthetically with Cy3 or Cy5. Two populations of labeled cRNA, a reference population and an experimental population, were compared with each other by competitive hybridization to microarrays. Two hybridizations were done with each cRNA sample pair using a fluorescent dye reversal strategy. Human microarrays contained oligonucleotide probes corresponding to approximately 21,000 genes. All oligonucleotide probes on the microarrays were synthesized in situ with inkjet technology (Agilent Technologies, Palo Alto, CA). After hybridization, arrays were scanned and fluorescence intensities for each probe were recorded. Ratios of transcript abundance (experimental to control) were obtained following normalization and correction of the array intensity data. Gene expression data analysis was done with the Rosetta Resolver gene expression analysis software (version 7.0, Rosetta Biosoftware, Seattle, WA).

Project description:Background and Objectives: The Esophageal Adenocarcinoma Study Group Europe (EACSGE) recently proposed a granular histologic classification of esophageal-esophago-gastric junctional adenocarcinomas (EA-EGJAs) based on the study of naïve surgically resected specimens that, when combined with the pTNM stage, is an efficient indicator of prognosis, molecular events, and response to treatment. In this study, we compared histologic classes of endoscopic biopsies taken before surgical resection with those of the surgical specimen, to evaluate the potential of the EACSGE classification at the initial diagnostic workup. Methods: A total of 106 EA-EGJA cases with available endoscopic biopsies and matched surgical resection specimens were retrieved from five Italian institutions. Histologic classification was performed on all specimens to identify well-differentiated glandular adenocarcinoma (WD-GAC), poorly differentiated glandular adenocarcinoma (PD-GAC), mucinous muconodular carcinoma (MMC), infiltrative mucinous carcinoma (IMC), diffuse desmoplastic carcinoma, diffuse anaplastic carcinoma (DAC), and mixed subtypes. Related risk subgroups (low-risk versus high-risk) were also assessed. The correlations of histologic classes and risk subgroups between diagnostic biopsies and surgical resection specimens were explored with Spearman's correlation test. Sensitivity, specificity, accuracy, positive predictive value, negative predictive value, true positives, true negatives, false positives, and false negatives were also calculated. Results: A strong positive correlation between biopsies and surgical specimens occurred for both histologic classes (coefficient: 0.75, p < 0.001) and risk subgroups (coefficient: 0.65, p < 0.001). The highest sensitivities and specificities were observed for MMC, IMC, and DAC (100% and 99% for all), followed by WD-GAC (sensitivity 91%, specificity 79%) and PD-GAC (sensitivity 722%, specificity 86%). The low-risk and high-risk groups presented a sensitivity and specificity of 89% and 76% (low-risk) and 76% and 89% (high-risk). Conclusions: The EACSGE histologic classification of EA-EGJAs and associated prognostic subgroups can be reliably assessed on pre-operative diagnostic biopsies. Further studies on larger and more representative cohorts of EA-EGJAs will allow us to validate our findings and confirm if the EA-EGJA biopsy histomorphology and clinical TNM staging will be as efficient as the surgical specimen histomorphology and pTNM in predicting patient prognoses and tailoring personalized therapeutic approaches.

Dataset Information

Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma.

Publications

Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma.

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