Previous Malignancy as a Risk Factor for the Second Solid Cancer in a Cohort of Nuclear Workers

Осипов, М. В.; Sokolnikov, Mikhail

doi:10.28991/scimedj-2021-0301-2

Cited by 8 publications

(9 citation statements)

References 13 publications

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“…[23,24] The body's complex DNA repair system has evolved to correct DNA damage caused by the environment. [25] There are many DNA repair pathways, each responsible for repairing specific types of damage. [26] The base excision repair (BER) pathway mainly eliminates DNA damage caused by ionizing radiation, reactive oxygen radicals and methylation agents.…”

Section: Discussionmentioning

confidence: 99%

Association between APE1 rs1760944 and rs1130409 polymorphism with prostate cancer risk

et al. 2021

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Background:Recently, some studies have suggested that the association of apurinic/apyrimidinic endonuclease 1 (APE1) gene polymorphism with prostate cancer (PCa) risk, but there are still some controversies. Hence, we elaborated the relationship between APE1 rs1760944 and rs1130409 gene and PCa risk through systematic literature review and meta-analysis.Methods:As of March 2020, EMBASE, PubMed, the Cochrane Library, Science Direct/Elsevier, MEDLINE and CNKI were used for systematic literature retrieval to investigate the correlation between APE1 rs1760944 and rs1130409 gene polymorphism with PCa risk. Meta-analysis was performed using Review Manager and Stata software.Results:Seven studies were distinguished, consists of 1769 cases of PCa patients and 2237 normal controls. Our results illustrated that there are significant correlation between the APE1 rs1760944 gene polymorphism and PCa in all genetic models (P < .05). The combined odds ratios and 95% confidence intervals were as follows: Additive model (ORs 0.62, 95%, CI [0.39, 0.97]); Codominant model (ORs 0.74, 95% CI [0.58, 0.95]); Dominant model (ORs 0.75, 95%, CI [0.59, 0.95]); Recessive model (ORs 0.63, 95% CI [0.41, 0.96]); Allele model (ORs 0.78, 95% CI [0.65, 0.94]). There also have significant associations between APE1 rs1130409 polymorphisms and PCa in all genetic models (P < .05). The combined odds ratios and 95% confidence intervals were as follows: Additive model (ORs 1.37, 95%, CI [1.01, 1.85]); Codominant model (ORs 1.21, 95% CI [1.01, 1.44]); Dominant model (ORs 1.33, 95%, CI [1.02, 1.73]); Recessive model (ORs 1.74, 95% CI [1.06, 2.85]); Allele model (ORs 1.14, 95% CI [1.00, 1.29]).Conclusion:This study suggests that APE1 rs1760944 polymorphisms might be a protective factor of PCa, and APE1 rs1130409 is suggested to be a risk factor of PCa. APE1 rs1760944 and rs1130409 polymorphisms may be used in the risk assessment of PCa.

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Section: Discussionmentioning

confidence: 99%

Association between APE1 rs1760944 and rs1130409 polymorphism with prostate cancer risk

et al. 2021

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“…The etiology of SKCM is complex, and it is not completely clear. At present, researchers believe that DNA damage of skin pigment cells is the primary cause, and high-risk factors such as ultraviolet damage, radiation, previous malignancy, trauma stimulation, family history are the inducements of canceration [ 24 , 25 ]. The current diagnostic methods of cutaneous melanoma are reliable, including dermoscopy, ultrasound, and biopsy [ 2 , 26 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis identifies IFI16 as a novel signature associated with overall survival and immune infiltration of skin cutaneous melanoma

et al. 2021

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Background Skin cutaneous melanoma (SKCM) is the most common skin tumor with high mortality. The unfavorable outcome of SKCM urges the discovery of prognostic biomarkers for accurate therapy. The present study aimed to explore novel prognosis-related signatures of SKCM and determine the significance of immune cell infiltration in this pathology. Methods Four gene expression profiles (GSE130244, GSE3189, GSE7553 and GSE46517) of SKCM and normal skin samples were retrieved from the GEO database. Differentially expressed genes (DEGs) were then screened, and the feature genes were identified by the LASSO regression and Boruta algorithm. Survival analysis was performed to filter the potential prognostic signature, and GEPIA was used for preliminary validation. The area under the receiver operating characteristic curve (AUC) was obtained to evaluate discriminatory ability. The Gene Set Variation Analysis (GSVA) was performed, and the composition of the immune cell infiltration in SKCM was estimated using CIBERSORT. At last, paraffin-embedded specimens of primary SKCM and normal skin tissues were collected, and the signature was validated by fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC). Results Totally 823 DEGs and 16 feature genes were screened. IFI16 was identified as the signature associated with overall survival of SKCM with a great discriminatory ability (AUC > 0.9 for all datasets). GSVA noticed that IFI16 might be involved in apoptosis and ultraviolet response in SKCM, and immune cell infiltration of IFI16 was evaluated. At last, FISH and IHC both validated the differential expression of IFI16 in SKCM. Conclusions In conclusion, our comprehensive analysis identified IFI16 as a signature associated with overall survival and immune infiltration of SKCM, which may play a critical role in the occurrence and development of SKCM.

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“…These oncological effects without the impact of CT could be considered as "background" cases with zero CT dose for the further comparison. Since previous malignancy is an additional risk factor [12] the cases of second malignant tumours has not been used for the analyses even they appeared after the date of CT examination, and the follow-up period ended on the date of first malignancy.…”

Section: Cancer Incidence Calculationmentioning

confidence: 99%

Cancer Morbidity and Computed Tomography: “After” and “Due to” Challenge

Осипов¹,

Loginov²,

Melnikov³

et al. 2021

SciMed. J.

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The article discusses the problem of carcinogenic risk assessment in the context of relationship with diagnostic radiation resulted from Computed Tomography (CT). The study aimed to evaluate the possible long-term carcinogenic effects after the exposure to a low dose of diagnostic radiation, appeared within a decade after the 1st CT scan. Information on patients examined using CT in the District Hospital of Kasli (KDH) has been derived from the CT archives since 2009 when the first CT examinations has been performed in the KDH. The data were linked to local Cancer registry, the Death registry, and the “CT Registry” database (CTDB) to obtain the information on vital status, the cause of death, cancer morbidity and CT examinations outside KDH, respectively. 275 CT examinations of 246 patients have been recorded to the data file (KDH cluster). To the end of the study, 46 cases of malignant tumours (MT) have been accumulated in the study group. The average observation time was 6.5 years (90% CI 6.2-6.8). The distribution of cancers among patients exposed to CT has been shown retrospectively through the date of birth of patient to December, 31, 2018. The cases of MT diagnosed prior to 1st CT examination have been excluded from the analyses. Cancer-related conditions stated before the date of 1stCT examination have been accounted. The cumulative cancer incidence after the exposure to CT, adjusted for predisposed conditions in the study group was 4.8%. The study results have been compared with the results of the LSS cohort study to assess the expected excess cancer morbidity. The data obtained in the study provide the information for a comprehensive epidemiological assessment of long-term effects related to diagnostic radiation exposure in the Ozyorsk Computed Tomography Cohort (OCTC study). Doi: 10.28991/SciMedJ-2021-0304-3 Full Text: PDF

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Previous Malignancy as a Risk Factor for the Second Solid Cancer in a Cohort of Nuclear Workers

Cited by 8 publications

References 13 publications

Association between APE1 rs1760944 and rs1130409 polymorphism with prostate cancer risk

Association between APE1 rs1760944 and rs1130409 polymorphism with prostate cancer risk

Comprehensive analysis identifies IFI16 as a novel signature associated with overall survival and immune infiltration of skin cutaneous melanoma

Cancer Morbidity and Computed Tomography: “After” and “Due to” Challenge

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