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Record W4414286893 · doi:10.14740/wjon2631

Problems in Cancer Genome Medicine: Base Mutations Cause Intron Start Signals, Resulting in Unexpected Splicing

2025· article· en· W4414286893 on OpenAlexvenueno aff
Takuma Hayashi, Ikuo Konishi

Bibliographic record

VenueWorld Journal of Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
FundersChugai PharmaceuticalUniversity of TokyoSysmex Corporation
KeywordsGeneRNA splicingCancerIntronMutationGenomeGenetic testing

Abstract

fetched live from OpenAlex

Background: The genetic characteristics of surgically removed cancerous tissues are examined using cancer gene panel testing in cancer genome medicine to detect the pathogenic variants involved in the proliferation and progression of cancer cells. An antitumor drug is prescribed if it directly acts on the detected pathogenic variant; however, some aspects require careful consideration by medical professionals in such cases. The genetic mutations involved in the progression or onset of malignant tumors differ with race. Furthermore, genetic mutations that are variants of unknown significance (VUS) may be involved in the progression or onset of malignant tumors in some races according to the ClinVar results from the National Center for Biotechnology Information. Single nucleotide variations can result in silent mutations or splice sites. Methods: We therefore reexamined the CGP results (VUS) of patients suspected of developing hereditary tumors based on their family background using IGV and RT-PCR. Results: KRAS Q61K, which is found in many gastrointestinal cancers, was identified as a VUS by ClinVar, but this gene mutation was found to cause splicing. The cancer gene panel test of a 41-year-old male patient with paraganglioma identified succinate dehydrogenase complex, iron-sulfur subunit B (SDHB) G642T as a VUS. However, this mutation was later discovered to cause the splicing site to shift, preventing SDHB from translating from the correct mRNA. In addition, a cancer gene panel test of a 47-year-old patient with right breast cancer determined that breast cancer susceptibility gene 2 (BRCA2) 631 3A>T was a VUS. However, this mutation may create a splicing site, which means that the correct BRCA2 mRNA for BRCA2 is not produced. Conclusions: The diagnosis of gene mutations based on the results of cancer gene panel testing may not always be correct, and a detailed examination of gene mutations is necessary. Our medical staff has performed cancer gene panel testing on approximately 5,500 cases of intractable malignant tumors to date and are investigating new treatments for these tumors. In this article, we discuss our experience with cancer gene panel testing as well as the problems encountered and new findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.373
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueWorld Journal of OncologySame topicGenetic factors in colorectal cancerFrench-language works237,207