ArticleFrontiers in oncology2021
Measurement of Circulating Tumor Cells to Track Hepatocellular Carcinoma Progression After Liver Transplantation-Case Report.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Circulating tumor DNA as a predictive biomarker for prognosis in hepatocellular carcinoma: a systematic review and meta-analysis.Journal of the National Cancer Center · 2026Article
- Serial circulating tumor DNA profiling predicts tumor recurrence after liver transplantation for liver cancer.Hepatology international · 2024Article
- Lytic efficiency of immunosuppressive drug-resistant armoured T cells against circulating HBV-related HCC in whole blood.Immunotherapy advances · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Management of patients with hepatocellular carcinoma (HCC) largely relies on surgery and other systemic therapies. However, the poor diagnosis of cancer recurrence or metastasis can lead to a high frequency of treatment failure. Thus, factors that can predict disease status and prognosis of patients need to be identified. Circulating tumor cells (CTCs) are known to accurately predict survival of patients. Here, we report a case in which CTCs successfully predicted the progression of metastatic colon polyps after interventional therapy for HCC. A 48-year-old man was diagnosed with HCC with moderate differentiation in 2016 and subsequently underwent orthotopic liver transplantation. Discharge medications were continued with immunosuppressants (tacrolimus) and antiviral drugs (Titin). In 2018, a colon polyp, a type of tubular adenoma, was detected and surgically removed. However, in 2020, the same tubular adenoma recurred. During cancer progression, CTC counts were measured to monitor the status of metastasis, and a positive correlation was noted between the dynamic change in CTC counts and cancer response (metastasis or recurrence). When diagnosing the metastatic adenoma, the number of cytokeratin-positive CTCs was significantly increased; however, it dropped to zero after the polyp was surgically removed. The same change in CTC counts was observed during the second recurrence of the adenoma, and a subgroup of CTCs, cell surface vimentin-positive CTCs, was significantly increased. The CTC count dropped to an undetectable level after the surgery for the first time. In summary, we presented a clinical case in which CTC counts could predict disease progression during HCC metastasis. Thus, CTC counts should be measured after liver transplantation in patients with HCC for diagnosis and clinical decision-making as it is effective in monitoring cancer progression.
Indexed as
Identifiers
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.