DEPENDENCE OF OVERALL AND RELAPSE-FREE PATIENTS SURVIVAL FROM MOLECULAR GENETIC SUBTYPE OF ESOPHAGEAL SQUAMOUS CELL CANCER
Bibliographic record
Abstract
Esophageal squamous cell carcinoma (ESCC) is a group of heterogeneous tumors with a different prognosis. In recent years, various molecular signatures of ESCC have been identified, which are different in different populations. The aim of the study was the molecular typing of ESCC patients in southern Russia and the assessment of patient survival, taking into account the identified tumor molecular genetic subtype. The material for the study was the sections of FFPE-blocks of 124 patients with ESCC. Tumor and non-tumor esophagus cells isolation was carried out by laser microdissection with contactless capture. 248 DNA samples were extracted from the cells by the phenol-chloroform method. For molecular typing of ESCC, the relative copy number variation (CNV) of 8 genes (CUL3, ATG7, SOX2, TP63, YAP1, VGLL4, CDK6, KDM6A) was determined by Real-Time qPCR and 7 single nucleotide polymorphisms (SNP) (NFE2L2 (c.85G> A), NOTCH1 ( c.1379C> T), NOTCH1 (c.1451G> T), ZNF750 (c.414C> A), ZNF750 (c..1621G> A), SMARCA4 (p.Q758 *, c.2272C> T), KMT2D (Q5170 *, c.15508C> T)) were determined by the method of Sanger direct sequencing. During the study, in ESCC patients of the Southern Russia population identified SNP in genes NFE2L2, NOTCH1, SMARCA4, KMT2D and CNV of genes CUL3, ATG7, SOX2, TP63, YAP1, VGLL4, CDK6 and KDM6A, earlier described for populations of Eastern Europe, Canada and the USA. Three molecular genetic subtypes of ESCC were verified, based on the differences in SNP and CNV of these genes: ESCC1 was verified in 31.5%, ESCC2 in 66.1%, and ESCC3 in 2.4% of patients. At the same time, higher survival rates were established in ESCC patients with the molecular genetic subtype ESCC2, as compared with ESCC1 and ESCC3. Differences in survival between the three groups were statistically significant (p = 0.00001). Thus, the determination of the molecular genetic subtype of ESCC is an important approach to improve the prediction of the course of this disease and the possibility of adjusting the appropriate therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".