ReviewProtein & cell2026
Advances in multi-omics for esophageal squamous cell carcinoma: diagnostic, prognostic, and therapeutic perspectives.
Review in Protein & cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Prognostic significance of DNA damage response-related markers in esophageal squamous cell carcinoma using machine learning approaches.Journal of gastrointestinal oncology · 2026Article
- Multi-Omics and Molecular Simulation Identify KIF11 as a Candidate Direct Target of Resveratrol in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in radiotherapy, chemotherapy, and immunotherapy. The marked interpatient and intratumor heterogeneity of ESCC underscores the need for molecularly informed diagnostic and therapeutic strategies. Recent high-throughput omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have substantially advanced our understanding of ESCC biology. Genomic profiling has revealed recurrent alterations such as TP53 and NOTCH1 mutations, as well as actionable targets including PIK3CA, FGFR1, and SOX2 amplifications, which provide new opportunities for precision therapy. Epigenomic and transcriptomic analyses have identified methylation-based early detection markers (e.g., PAX9, SIM2) and immune-related transcriptomic subtypes associated with prognosis and immunotherapy responsiveness. Proteomic and metabolomic studies have further uncovered cell cycle and spliceosome pathway activation and altered lactate metabolism, offering additional biomarker and therapeutic insights. In this review, we synthesize these multi-omics advances and highlight how they collectively inform improved diagnostic, prognostic, and therapeutic strategies for ESCC. Despite these developments, the clinical translation of multi-omics findings remains limited due to the lack of standardized analytical pipelines, insufficient multicenter validation, and the high cost and technical complexity of integrating multi-omics data into routine clinical workflows. Future research integrating artificial intelligence with multi-omics data holds promise for enhancing diagnostic accuracy and enabling more precise therapeutic decision-making in ESCC.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.