CN117789976A - Application of detecting chromosome segment information in extrahepatic transfer prediction of primary liver cancer patient - Google Patents
Application of detecting chromosome segment information in extrahepatic transfer prediction of primary liver cancer patient Download PDFInfo
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Abstract
The invention belongs to the field of prognosis of extrahepatic transfer of primary liver cancer, and relates to application of chromosome deletion in extrahepatic transfer prediction of primary liver cancer. The invention finds that the deletion of chromosome segments 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p and 22q is significantly enriched in a metastasis from the perspective of clone evolution. Calculating the number of the 7 deletion variants in the primary focus as a risk score, and finding that metastatic cancer has a higher risk score than primary liver cancer; meanwhile, the time for extrahepatic metastasis of the patient with the primary cancer with higher risk score is shorter, and 7 deletion variants are suggested to be used as risk prediction factors for extrahepatic metastasis after primary liver cancer surgical excision. Furthermore, single-and multi-factor analysis found that 7 deletion variants have stable predictive power for the risk of metastasis for patients in different data sets. Therefore, the chromosome copy number variation of the primary tumor is a prediction index of extrahepatic metastasis after the surgical excision of the primary liver cancer, and is a possible treatment target for preventing extrahepatic metastasis in the future.
Description
Technical Field
The invention belongs to the field of extrahepatic transfer prognosis of primary liver cancer, and relates to application of detection chromosome segment information in extrahepatic transfer prediction of primary liver cancer patients.
Background
Somatic cell copy number variation can be used for early diagnosis of tumors and genetic screening of newborns. The bladder cancer kit (UroVysion kit) is intended to detect aneuploidy of chromosome 3, chromosome 7, and chromosome 17 and the absence of 9p21 in a urine sample of a haematuria patient suspected of having bladder cancer by Fluorescence In Situ Hybridization (FISH). Copy number variation is the second largest genetic factor responsible for birth defects in newborns, so prenatal screening is essential. The current prenatal noninvasive screening is clinically directed only to trisomy 21, trisomy 18 and trisomy 13.
However, in the currently marketed cancer detection kit, there is little concern about chromosome arm-level copy number variation. In the extrahepatic transfer risk prediction of primary liver cancer patients, the detection information of chromosome segments is not reported in the related art as a risk prediction factor.
Disclosure of Invention
In order to overcome the technical problems, the invention provides application of detecting chromosome segment information in extrahepatic transfer prediction of a primary liver cancer patient.
In a first aspect, the invention provides the use of a detection reagent for detecting the deletion of copy number information of chromosome segments, 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p, 22q, in the preparation of a product for predicting risk of extrahepatic metastasis in a primary liver cancer patient.
By adopting the technical scheme, the invention discovers that the deletion of chromosome sections 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p and 22q is remarkably enriched in metastatic cancers from the aspect of clone evolution through researching the amplification and deletion change conditions of small fragments and chromosome arm length level genes.
Further, the product is a kit or a detection device.
Further, the risk prediction comprises the steps of:
step a) assessing the copy number of the chromosomal segment in the tumor tissue of the primary liver cancer patient; step b) comparing the evaluation result of step a) with the chromosome segment in normal human tissue; and step c) if a copy number variation of the chromosome segment or a chromosome segment deletion occurs, the patient is at higher risk of extrahepatic metastasis after surgical excision of the primary liver cancer.
In a second aspect, the invention also provides a detection kit or a detection device for predicting the prognosis of extrahepatic transfer risk of a primary liver cancer patient, wherein the detection kit or the detection device comprises a detection reagent for detecting copy number information of chromosome segments.
Further, the chromosome segment is 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p, 22q.
Compared with the prior art, the invention has the following technical effects:
1) The invention discovers that the deletion of chromosome segments 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p and 22q is remarkably enriched in metastatic cancers from the aspect of clone evolution through researching the amplification and deletion change conditions of small fragments and chromosome arm length level genes. Calculating the number of the 7 deletion variants in the primary focus as a risk score, and finding that metastatic cancer has a higher risk score than primary liver cancer; meanwhile, the time for extrahepatic metastasis of the patient with the primary cancer with higher risk score is shorter, and 7 deletion variants are suggested to be used as risk prediction factors for extrahepatic metastasis after primary liver cancer surgical excision.
2) The invention also discovers that 7 deletion variants have stable prediction capability on the transfer risks of patients in different data sets through single-factor and multi-factor analysis. Therefore, the chromosome copy number variation of the primary tumor is a prediction index of extrahepatic metastasis after the surgical excision of the primary liver cancer, and is a sexual treatment target for preventing extrahepatic metastasis in the future.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly described below.
FIG. 1 weighted genomic instability index (wGII) of Primary (PT) and Metastatic (MT) liver cancer samples. (A) wGII in PT of patients in extrahepatic transfer group (MET) and non-metastatic relapse group (NRM) was found in the queue (discovery method). (B) wGII in PT and MT of patients in extrahepatic transfer group was found in the cohort. The P-value was from unpaired double-ended Wilcoxon rank sum test.
FIG. 2 is a proportion of the number of times each local (A) or chromosome arm SCNA (B) occurs in "selected for transfer" and "non-selected for transfer" subclones in the extrahepatic transfer group of the discovery cohort. The right panel shows the degree of enrichment of each local or chromosome arm grade SCNA event in "selected for transfer" and "not selected for transfer" subclones, shown with log10 p values. The P value was calculated using a binomial test and corrected using the Benjamini-Hochberg method.
FIG. 3Met SCNAs is related to the prognosis of metastasis in patients. (A) Met SCNAs number in the found MT and PT in the queued extrahepatic transfer group, and PT in the non-transfer relapse group. The data points represent the maximum number of Met SCNAs in the patient PT or MT. The P-value was from unpaired double-ended Wilcoxon rank sum test. (B) Kaplan-Meier curves based on the shift survival time to find Met scNAs status (higher and lower) of patient PT in the cohort. (C) Kaplan-Meier curves based on progression free survival time of Met scNAs status of patient PT in TCGA LIHC cohorts. Patients with an allogeneic metastasis were included in the (B) and (C) analyses.
Figure 4 finds single and multi-factor Cox regression analysis of transfer time related factors in the queue.
FIG. 5 risk prediction of extrahepatic metastasis of patients by Met SCNAs in validation cohorts. (A) wGII in PT in patients in the extrahepatic transfer group and in the non-transfer relapse group were validated. The P-value was from unpaired double-ended Wilcoxon rank sum test. (B) Kaplan-Meier curves based on the transition survival time of Met SCNAs status of patient PT in validation cohorts. Patients with a differential time shift were included in the analysis. (C) And verifying single-factor Cox regression analysis of transfer time related factors in the queue.
Detailed Description
The invention will be better understood from the following examples. However, it will be readily appreciated by those skilled in the art that the description of the embodiments is provided for illustration and explanation of the invention only and is not intended to limit the invention as described in detail in the claims. Unless otherwise indicated, reagents, methods and equipment employed in the present invention are conventional methods and test materials used, unless otherwise indicated, are available from commercial companies.
Example 1
The surgical excision specimens of 109 primary liver cancer patients are collected as a discovery queue, according to follow-up information, the postoperative extrahepatic metastasis, the absence of metastasis or recurrence of the patients in the discovery queue are 78 cases and 31 cases respectively, and the collected tumor samples are subjected to whole exon sequencing.
Somatic copy number changes (SCNAs) of liver cancer specimens were deduced using the sequencer (v2.1.2) and gistick (v 2.0) software. By calculating the weighted genome instability index (wGII), as shown in fig. 1, it was found that in the cohort, primary liver cancer of extrahepatic transfer patients showed a significant increase in wGII compared to non-transfer-recurrence patients (median of extrahepatic transfer group is 0.41, median of non-transfer-recurrence group is 0.29, p=0.0067), indicating that liver cancer SCNA load of extrahepatic transfer patients is higher compared to non-transfer-recurrence patients. The overall genomic instability in liver cancer extrahepatic metastases was significantly increased (median of the metastatic samples was 0.48, median of the primary samples was 0.41, p=0.027), suggesting that somatic cell copy number variation events may play a key role in affecting the metastatic potential of liver cancer.
Example 2
Primary tumors typically have a high intratumoral heterogeneity, i.e., there are multiple tumor subcloned cell populations with genetic differences, and typically only a portion of the subcloned cell populations have metastatic capacity and generate distant metastases. Using multi-region sampling and phylogenetic reconstruction, the progress of individual clones from primary to metastatic sites, or from recurrent sites to metastatic sites, was analyzed. All copy number variations are classified into three categories based on the pattern of somatic mutations in primary and paired metastases: selected (selected) by the metastasis, unselected (unselected) by the metastasis, inherited (main). Variations that are present only in the metastasis (subcloning mutations) but not in the paired primary or recurrent foci are not defined as selected, as they may be obtained after cancer cells colonize the metastatic site without affecting the progression of cancer cell metastasis. From each focal/Arm level SCNA in the extrahepatic transfer dataset, we can calculate the ratio of selected, unselected and main from paired primary and primary-derived metastases, recurrent and recurrent-derived metastases. The ratio selected by the metastases can be calculated by selected/(selected+unselected) to further screen for the variation enriched in the metastases.
Arm level SCNAs (q < = 0.05) significantly enriched in public dataset (Cancer Genome Atlas Research Network,2017; gao et al, 2019) or in metastases of extrahepatic metastases dataset were defined as driving Arm level SCNAs (n.driver=34, n.passenger=46). Focal level SCNAs, which is significantly enriched in primary focus samples found in the queued extrahepatic transfer dataset, is also divided into two classes: focal level SCNAs verified in any of four public datasets (Wang et al, 2013;Cancer Genome Atlas Research Network,2017;Gao et al, 2019; zhou et al, 2019) is defined as driver focal level SCNAs (n.driver=22, n.passenger=13). The background probability, i.e. the probability that passenger SCNAs are selected by the metastasis, is calculated based on finding all passenger (passenger) SCNAs in the queue extrahepatic transfer data set. The proportion of "selected" events is then compared to the proportion of "unselected" based on a binomial test, the background probability p= 0.4964,Arm level SCNAs of focal level SCNAs, and the background probability p= 0.4928.3 drives focal level SCNAs (11p15.5, 14q32.33, and 4q35.2) and 4 drives Arm level SCNAs (14 q, 19p, 21p, and 22 q) were significantly enriched in metastases, suggesting that these 7 copy number variations might promote metastatic progression of liver cancer (fig. 2).
Example 3
Early stage, by comparing the primary foci of extrahepatic transfer patients in the discovery cohort and SCNA conditions in the metastases, 7 SCNA events were found to be enriched in the metastatic tumors of extrahepatic transfer patients. Given the complexity and multiple steps of cancer metastasis processes, a single metastatic selected SCNA may not be sufficient to complete the entire metastasis process. We defined 7 copy number variations significantly enriched in metastases as Met SCNAs and calculated the number of 7 Met SCNAs in primary foci of the patient as risk scores. Compared to primary foci, the foci of extrahepatic transfer patients had significantly higher risk scores (fig. 3a, p=0.0038). Consistently, primary foci with metastatic clinical outcome showed significantly higher risk scores (p=0.0077) compared to primary foci from the non-metastatic recurrent group. In the discovery queue, the median of risk scores for all primary foci is defined as the threshold. If the number of Met SCNAs in the primary focus is greater than or equal to the threshold, the patient is classified as higher Met SCNAs, otherwise the patient is classified as lower Met SCNAs. The same method is also applicable to TCGA LIHC queues. In consideration of clinical practical application value and reduction of prediction bias, 79 patients in total were found in the cohort after the patients with primary tumor and metastasis were removed from the analysis, 48 cases of extrahepatic metastasis were found, and 31 cases of extrahepatic metastasis were not found (non-metastatic recurrent patients). In the discovery cohort (p=0.0001), patients with differential metastasis with higher Met SCNAs counts for primary foci (median of Met SCNAs counts for all patients primary foci in the sample set or greater) exhibited significantly shorter metastasis times (fig. 3B). In the public dataset TCGA LIHC, patients with higher Met SCNAs counts also exhibited worse progression free survival (p=0.027) (fig. 3C). Multi-factor combination analysis of these 7 SCNA events with the time to distant metastasis following primary liver cancer excision showed statistically significant prognostic impact of met_scnas (fig. 4). The above results suggest that the SCNA event of the primary tumor is a predictor of extrahepatic metastasis after surgical excision of the primary liver cancer, and even a possible therapeutic target for future prevention of extrahepatic metastasis.
Application examples
To further verify the prognosis of Met_SCNAs for metastasis in patients, we also collected 65 primary tumors as a verification cohort, 41 patients developed extrahepatic metastasis during follow-up, and 24 patients developed neither metastasis nor intrahepatic recurrence. Consistently, primary liver cancer in extrahepatic transfer patients showed a significant increase in wGII (median of 0.32 in extrahepatic transfer group, median of 0.20 in non-transfer recurrence group, p=0.018) compared to non-transfer recurrence patients, suggesting higher SCNA burden in extrahepatic transfer patients (fig. 5A). By counting Met SCNAs counts in each sample, it was found that patients with orthotopic metastasis with higher Met SCNAs counts in the validation cohort (p=0.047) exhibited significantly shorter metastasis times (fig. 5B). Furthermore, single factor analysis showed that met_scnas also had a statistically significant effect on patient transfer time in the validation cohort (fig. 5C).
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims.
Claims (5)
1. Use of a reagent for detecting copy number information of a chromosomal segment, wherein the chromosomal segment is 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p, 22q, for the preparation of a product for predicting risk of extrahepatic metastasis in a primary liver cancer patient.
2. The use according to claim 1, wherein the product is a kit or a detection device.
3. The use according to claim 1, wherein the risk prediction comprises the steps of:
step a) assessing the copy number of the chromosomal segment in the tumor tissue of the primary liver cancer patient;
step b) comparing the evaluation result of step a) with the chromosome segment in normal human tissue; and
step c) if the copy number variation of the chromosome segment or the chromosome segment deletion occurs, the risk of extrahepatic metastasis of the patient after the primary liver cancer is surgically excised is higher.
4. A detection kit or detection device for predicting extrahepatic transfer risk of a primary liver cancer patient is characterized in that the detection kit or detection device comprises a detection reagent for detecting copy number information of chromosome segments.
5. The test kit or test device of claim 4, wherein the chromosome segment is 11p15.5, 14q32.33, 4q35.2, 14q, 19p, 21p, 22q.
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