Cancer Informatics最新文献

This review discusses the possible involvement of infections-associated cancers in humans, with virus infections contributing 15% to 20% of total cancer cases in humans. DNA virus encoded proteins interact with host cellular signaling pathways and control proliferation, cell death and genomic integrity viral oncoproteins are known to bind cellular Deubiquitinates (DUBs) such as cyclindromatosis tumor suppressor, ubiquitin-specific proteases 7, 11, 15 and 20, and A-20 to improve their intracellular stability and cellular signaling pathways and finally transformation. Human papillomaviruses (cervical carcinoma, oral cancer and laryngeal cancer); human polyomaviruses (mesotheliomas, brain tumors); Epstein-Barr virus (B-cell lymphoproliferative diseases and nasopharyngeal carcinoma); Kaposi's Sarcoma Herpesvirus (Kaposi's Sarcoma and primary effusion lymphomas); hepatitis B (hepatocellular carcinoma (HCC)) cause up to 20% of malignancies around the world.

The relevance of nongenetic factors to prostate cancer (PCa) has been elusive. We aimed to quantify the contributions of environmental factors to PCa and identify risk-related diet metrics and relevant racial disparities. We performed a unique analysis of the Diet History Questionnaire data of 41 830 European Americans (EAs) and 1282 African Americans (AAs) in the PLCO project. The independent variables in the regression models consisted of age at trial entry, race, family history of prostate cancer (PCa-fh), diabetes history, body mass index (BMI), lifestyle (smoking and coffee consumption), marital status, and a specific nutrient/food factor (X). P < .05 and a 95% confidence interval excluding zero were adopted as the criteria for determining a significant difference (effect). We established a priority ranking among PCa risk-related genetic and environmental factors according to the deviances explained by them in the multivariate Cox-PH regression analysis: age > PCa-fh > diabetes ⩾ race > lifestyle ⩾marital-status ⩾BMI > X. We confirmed previous studies showing that (1) high protein and saturated fat levels in diet were related to increased PCa risk, (2) high-level supplementary selenium intake was harmful rather than beneficial for preventing PCa, and (3) supplementary vitamin B6 was beneficial for preventing benign PCa. We obtained the following novel findings: high-level organ meat intake was an independent predictor for increased aggressive PCa risk; supplementary iron, copper and magnesium increased benign PCa risk; and the AA diet was "healthy" in terms of the relatively lower protein and fat levels and was "unhealthy" in that it more commonly contained organ meat. In conclusion, we established a priority ranking among the contributing factors for PCa and identified several risk-related diet metrics and the racial disparities. Our findings suggested some new approaches to prevent PCa such as restriction of organ meat intake and supplementary microminerals.

The second most frequent malignancy in women worldwide is cervical cancer. In the transformation(transitional) zone, which is a region of the cervix, columnar cells are continuously converting into squamous cells. The most typical location on the cervix for the development of aberrant cells is the transformation zone, a region of transforming cells. This article suggests a 2-phase method that includes segmenting and classifying the transformation zone to identify the type of cervical cancer. In the initial stage, the transformation zone is segmented from the colposcopy images. The segmented images are then subjected to the augmentation process and identified with the improved inception-resnet-v2. Here, multi-scale feature fusion framework that utilizes 3 × 3 convolution kernels from Reduction-A and Reduction-B of inception-resnet-v2 is introduced. The feature extracted from Reduction-A and Reduction -B is concatenated and fed to SVM for classification. This way, the model combines the benefits of residual networks and Inception convolution, increasing network width and resolving the deep network's training issue. The network can extract several scales of contextual information due to the multi-scale feature fusion, which increases accuracy. The experimental results reveal 81.24% accuracy, 81.24% sensitivity, 90.62% specificity, 87.52% precision, 9.38% FPR, and 81.68% F1 score, 75.27% MCC, and 57.79% Kappa coefficient.

[This corrects the article DOI: 10.1177/11769351231177267.].

It is increasingly recognized that the human immune response influences cancer risk, progression, and survival; consequently, there is growing interest in the role of human leukocyte antigen (HLA), genes that play a critical role in initiating the immune response, on cancer. Recent evidence documented clustering of cancers based on immunogenetic profiles such that breast and ovarian cancers clustered together as did uterine and cervical cancers. Here we extend that line of research to evaluate the HLA profile of those 4 cancers and their associations. Specifically, we evaluated the associations between the frequencies of 127 HLA alleles and the population prevalences of breast, ovarian, cervical, and uterine cancer in 14 countries in Continental Western Europe. Factor analysis and hierarchical clustering were used to evaluate groupings of cancers based on their immunogenetic profiles. The results documented highly similar immunogenetic profiles for breast and ovarian cancers that were characterized predominantly by protective HLA effects. In addition, highly similar immunogenetic profiles for cervical and uterine cancers were observed that were, conversely, characterized by susceptibility effects. In light of the role of HLA in host immune system protection against non-self antigens, these findings suggest that certain cancers may be associated with similar contributory factors such as viral oncoproteins or neoantigens.

Background: The molecular subtyping of breast cancer is related to estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). The present study aimed to systematically analyze the expression, function, and prognostic value of ER, PR, HER2, and their prevalence in different ethnic groups and among Bangladeshi breast cancer (BC) patients.

Method: This study included 25 BC patients and 25 healthy controls, aged between 25 and 70 years. The study characteristics were compared using the ANOVA and Chi-square tests. Also, the multi-Omics dataset of 775 BC patients from TCGA was analyzed for ER, PR, and HER2 in breast cancer subtypes and compared among different ethnicities.

Results: For most BD breast cancer cases, the age at diagnosis was ⩾40 years, had only a histopathological diagnosis (P-value .004), and no history of mammography or other pathological tests. For treatment, had only chemotherapy (P-value .004) and no hormone therapy (P-value <.001). The majority of patients (>60%) were of stage-II cancer and TNBC (40%) subtype. The BC ethnicity-stratified data of ER, PR, and HER2 indicated a strong correlation across all ethnicities (P-value 4.99e-35; P-value 3.79e-18). The subtypes stratified data indicated a higher percentage of Luminal A (58.3%) in Caucasians whereas Luminal B (24.3%) and HER2 (25.2%) subtypes were found higher in Asians and TNBC (36.0%) were found in Africans. However, a significantly higher frequency of TNBC (52.2%) compared to Asians (14.8%) was found in BD patients (P-value <.001). The overall survival analysis of BC subtypes demonstrated that Luminal B (P-value .005) and HER2 enriched (P-value .015) were significantly more aggressive and were dominant in the Asian population.

Conclusion: A significant association was found between BC subtypes with different ethnicities and Bangladeshi women and these findings might aid in the prevention, management, and raising of awareness against risk factors in the near future.

Iron is an essential cofactor needed for normal functions of various enzymes and its depletion lead to increase DNA damage, genomic instability, deteriorate innate, adaptive immunity, and promote tumor development. It is also linked to tumorigenesis of breast cancer cells through enhancing mammary tumor growth and metastasis. There is insufficient data describing this association in Saudi Arabia. This study aims to determine the prevalence of iron deficiency and its association with breast cancer among premenopausal and postmenopausal women referred for breast cancer screening center in Al Ahsa, Eastern Province of Saudi Arabia. Age, hemoglobin level, iron level, history of anemia, or iron deficiency were collected from patients' medical records. The included participants were grouped based on their age into premenopausal (<50 years) or postmenopausal (⩾50 years). The definition of low Hb implemented (Hb below 12 g/dL) and low total serum Iron levels (below 8 μmol/L). Logistic regression test was used to compute the association between having a positive cancer screening test (radiological or histocytological) and participant's lab results. The results are presented as odds ratios and 95% confidence intervals. Thrree hundred fifty-seven women were included, 77% (n = 274) of them were premenopausal. This group cases had more history of iron deficiency (149 [60%] vs 25 (30%), P = .001) compared to those in the postmenopausal group. The risk of having a positive radiological cancer screening test was associated with age (OR = 1.04, 95% CI 1.02-1.06), but negatively was associated with iron level (OR = 0.9, 95% CI 0.86-0.97) among the entire cohort. This study is the first to propose an association between iron deficiency and breast cancer among Saudi young females. This could suggest iron level as a new risk factor that may be used by clinicians to assess breast cancer risk.

Background: The Regional Basis of Solid Tumor (RBST), a clinical data warehouse, centralizes information related to cancer patient care in 5 health establishments in 2 French departments.

Purpose: To develop algorithms matching heterogeneous data to "real" patients and "real" tumors with respect to patient identification (PI) and tumor identification (TI).

Methods: A graph database programed in java Neo4j was used to build the RBST with data from ~20 000 patients. The PI algorithm using the Levenshtein distance was based on the regulatory criteria identifying a patient. A TI algorithm was built on 6 characteristics: tumor location and laterality, date of diagnosis, histology, primary and metastatic status. Given the heterogeneous nature and semantics of the collected data, the creation of repositories (organ, synonym, and histology repositories) was required. The TI algorithm used the Dice coefficient to match tumors.

Results: Patients matched if there was complete agreement of the given name, surname, sex, and date/month/year of birth. These parameters were assigned weights of 28%, 28%, 21%, and 23% (with 18% for year, 2.5% for month, and 2.5% for day), respectively. The algorithm had a sensitivity of 99.69% (95% confidence interval [CI] [98.89%, 99.96%]) and a specificity of 100% (95% CI [99.72%, 100%]). The TI algorithm used repositories, weights were assigned to the diagnosis date and associated organ (37.5% and 37.5%, respectively), laterality (16%) histology (5%), and metastatic status (4%). This algorithm had a sensitivity of 71% (95% CI [62.68%, 78.25%]) and a specificity of 100% (95% CI [94.31%, 100%]).

Conclusion: The RBST encompasses 2 quality controls: PI and TI. It facilitates the implementation of transversal structuring and assessments of the performance of the provided care.