ArticlePloS one2021
Genomic analysis for the prediction of prognosis in small-bowel cancer.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Immunohistochemical "null" pattern of all four mismatch repair proteins in Lynch syndrome-associated small bowel adenocarcinoma: a case report and comprehensive genomic profiling.Virchows Archiv : an international journal of pathology · 2026Article
- Real-World Data of Comprehensive Genomic Profiles and Clinicopathological Characteristics of Duodenal Epithelial Neoplasms.Cancers · 2026Article
- A retrospective analysis of taxane-based chemotherapy in small bowel adenocarcinoma.The oncologist · 2026Article
- Clinicopathological features and prognosis of primary small bowel adenocarcinoma: a large multicenter analysis of the JSCCR database in Japan.Journal of gastroenterology · 2024Article
- Potential biomarkers and immune characteristics of small bowel adenocarcinoma.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current understanding of clinicopathological features and genomic variants of small-bowel cancer is limited, in part due to the rarity of the disease. However, understanding of these factors is necessary for the development of novel therapeutic agents for small-bowel cancer. Thus, we aimed to identify the clinicopathological features and genomic variants associated with its prognosis and recurrence. We retrospectively examined 24 consecutive patients with primary small-bowel cancer surgically treated between May 2005 and August 2018 and collected 29 tumor specimens. The 29 lesions were subjected to mismatch repair status evaluation, using immunohistochemistry (IHC), and targeted genomic sequencing, after which they were analyzed using a panel of 90 cancer-related genes. IHC revealed that 45% (13/29) of the lesions exhibited deficient mismatch repair. The most common genomic variants in small-bowel cancers were in TP53 (48%, 13/27), followed by KRAS (44%, 12/27), ARID1A (33%, 9/27), PIK3CA (26%, 7/27), APC (26%, 7/27), and SMAD4, NOTCH3, CREBBP, PTCH1, and EP300 (22%, 6/27 each). Overall survival and disease-specific survival of patients with tumor mutational burden (TMB) ≥10 mutations/Mb (n = 17) were significantly better than those of patients with TMB <10 mutations/Mb (n = 6). Additionally, patients with a mutant SMAD4 had poorer recurrence-free survival than those with wild-type SMAD4. Our results suggested that TMB and SMAD4 mutations were associated with the prognosis of small-bowel cancer patients. Thus, cancer genomic analysis could be useful in the search for biomarkers of prognosis prediction in small-bowel cancers.
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.