Novel polymorphisms in caspase-8 are associated with breast cancer risk in the California Teachers Study

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

Objective: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC). Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. Molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of significant genes was undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from the logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of a robust model, and a nomogram was constructed with the independent predictors for pCR rate. Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response. Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.

The Associations of Common Genetic Susceptibility Variants with Breast Cancer in Jordanian Arabs: A Case-Control Study

OBJECTIVE

In Jordan, breast cancer (BC) affects a substantial proportion of Jordanian women, highlighting the need for studies to be carried out regarding the genetic component of the disease. The aim of the present study was to investigate the interaction between BC risk and prognosis and polymorphisms in genes (ATM, CASP8, FGFR2, FN1, IGF1, LSP1, MAP3K, MMP7, and RHOC) that were chosen for this study previously reported as having a role in the disease.

MATERIALS AND METHODS

Blood samples were collected from 242 BC patients and 231 disease-free volunteers recruited from the Jordanian population. DNA was extracted from blood and each sample was sent to the Australian Genome Research Facility for genotyping.

RESULTS

The rs1219648 SNP of the FGFR2 gene was the only investigated variant to show any direct association with BC in Jordanian women (p-value = 0.04). However, the CASP8rs6760993 SNP was found to be significantly associated with BC (p-value = 0.04) when using the dominant model. Other gene polymorphisms showed varying levels of association between some investigated SNPs and different BC risk and prognostic factors.

CONCLUSION

Despite reports to the contrary in other populations, most of the investigated genes and their respective SNPs did not show any significant association with BC in Jordanian women. Our results underline the need for independent BC research to be carried out in the Jordanian population to decipher the genetic basis of the disease.
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Association of CASP8 polymorphisms and cancer susceptibility: A meta-analysis

Caspase-8 plays is an essential enzyme in apoptosis pathway. Several investigation have been done to identify the relation between CASP8 polymorphisms and different human cancers, but, the findings are still debated. The aim of the current investigation is to assess if CASP8 rs3834129 (-652 6N insertion/deletion), rs1045485 G > C, rs3769818 G > A, rs6723097 A > C, rs3769821 T > C, rs13113 T > A, rs3769825 G > A, rs2293554 A > C, and rs10931936 C > T polymorphisms are linked to susceptibility of cancer. Our team has extracted the eligible studies up to July 4, 2019, from different sources. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were estimated to quantitatively evaluate the association between CASP8 polymorphisms and cancer susceptibility. Our results showed that the rs3834129 and rs1045485 polymorphisms meaningfully reduced the risk of cancer, while the rs3769818, rs3769821 and rs3769825 polymorphisms considerably increased cancer susceptibility. No association of rs6723097, rs13113, rs2293554 and rs10931936 polymorphisms was observed with cancer susceptibility. The CASP8 rs3834129 polymorphism reduced the risk of gastrointestinal, digestive tract, colorectal, breast and lung cancers. Furthermore, the cancer risk was decreased in Asian and Caucasian populations as well as population- and hospital-based studies due to this polymorphism. There was not any relation between this gene polymorphism and the risk of prostate and cervical cancer development. Regarding the CASP8 rs1045485 polymorphism, the reduced breast cancer risk along with the risk of cancer in Caucasians, population- and hospital-based studies were observed.

Cell-Cycle Cross Talk with Caspases and Their Substrates

Caspases play central roles in mediating both cell death and inflammation. It has more recently become evident that caspases also drive other biological processes. Most prominently, caspases have been shown to be involved in differentiation. Several stem and progenitor cell types rely on caspases to initiate and execute their differentiation processes. These range from neural and glial cells, to skeletal myoblasts and osteoblasts, and several cell types of the hematopoietic system. Beyond differentiation, caspases have also been shown to play roles in other "noncanonical" processes, including cell proliferation, arrest, and senescence, thereby contributing to the mechanisms that regulate tissue homeostasis at multiple levels. Remarkably, caspases directly influence the course of the cell cycle in both a positive and negative manner. Caspases both cleave elements of the cell-cycle machinery and are themselves substrates of cell-cycle kinases. Here we aim to summarize the breadth of interactions between caspases and cell-cycle regulators. We also highlight recent developments in this area.

Caspase-8: The double-edged sword

Caspase-8 is a cysteine - aspartate specific protease that classically triggers the extrinsic apoptotic pathway, in response to the activation of cell surface Death Receptors (DRs) like FAS, TRAIL-R and TNF-R. Besides it's roles in triggering death receptor-mediated apoptosis, Caspase-8 has also been implicated in the onsets of anoikis, autophagy and pyroptosis. Furthermore, Caspase-8 also plays a crucial pro-survival function by inhibiting an alternative form of programmed cell death called necroptosis. Low expression levels of pro-Caspase-8 is therefore associated with the malignant transformation of cancers. However, the long-held notion that pro-Caspase-8 expression/activity is generally lost in most cancers, thereby contributing to apoptotic escape and enhanced resistance to anti-cancer therapeutics, has been found to be true for only a minority of cancers types. In the majority of cases, pro-Caspase-8 expression is maintained and sometimes elevated, while it's apoptotic activity is regulated through different mechanisms. This supports the notion that the non-apoptotic functions of Caspase-8 offer growth advantage in these cancer types and have, therefore, gained renewed interest in the recent years. In light of these reasons, a number of therapeutic approaches have been employed, with the intent of targeting pro-Caspase-8 in cancer cells. In this review, we would attempt to discuss - the classic roles of Caspase-8 in initiating apoptosis; it's non-apoptotic functions; it's the clinical significance in different cancer types; and the therapeutic applications exploiting the ability of pro-Caspase-8 to regulate various cellular functions.

Association of Caspase-8 Genotypes With Oral Cancer Risk in Taiwan

BACKGROUND/AIM

Recently, mounting evidence has shown that caspase-8 (CASP8) rs3834129 (-652, 6N insertion/deletion) polymorphism may serve as a genetic biomarker for personal risk of various cancer types. The contribution of CASP8 rs3834129 polymorphism has been investigated in several oral cancer populations, but not in Taiwan. This study investigated the role of CASP8 rs3834129 polymorphism on oral risk in Taiwan.

MATERIALS AND METHODS

CASP8 rs3834129 polymorphic genotypes were determined and their associations with oral cancer risk were investigated among 788 patients with oral cancer and 956 age- and gender-matched healthy controls via polymerase chain reaction-restrictive fragment length polymorphism (PCR-RFLP) methodology. In addition, the interaction of CASP8 rs3834129 genotype with personal behavior and clinicopathological features were also examined.

RESULTS

The frequencies of II, ID and DD genotypes for CASP8 rs3834129 were 57.5, 36.5 and 6.0% in the patient group and 54.0, 39.0 and 7.0% in the healthy control group, respectively (p for trend=0.3052), genotypes were not significantly differentially distributed between the two groups. The comparisons in allelic frequency distribution also supported the findings that the D variant allele may not serve as a determinant of risk for oral cancer. There was no interaction of CASP8 rs3834129 genotype with age, gender, smoking, alcohol or betel quid consumption in regard to oral cancer risk.

CONCLUSION

Our results indicate that the caspase-8 genotype does not appear to play a direct role in personal susceptibility to oral cancer in Taiwan.

HMGB1 genetic polymorphisms are biomarkers for the development and progression of breast cancer

Breast cancer is a major cause of cancer mortality worldwide. High-mobility group box protein 1 (HMGB1) is a ubiquitous nuclear protein found in all mammal eukaryotic cells that participates in tumor progression, migration and metastasis. HMGB1 overexpression has been indicated in breast cancer patients. However, scant information is available regarding the association between HMGB1 single nucleotide polymorphisms (SNPs) and the risk or prognosis of breast cancer. We report on the association between 4 SNPs of the HMGB1 gene (rs1360485, rs1045411, rs2249825 and rs1412125) and breast cancer susceptibility as well as clinical outcomes in 313 patients with breast cancer and in 217 healthy controls. Patients with one G allele in the rs1360485 or rs2249825 domains are likely to progress to T2 tumor and lymph node metastasis. In addition, the presence of one G allele in SNPs rs1360485 or rs2249825 was associated with a higher risk of progressing to T2 tumor and distant metastasis amongst HER2-enriched and triple-negative breast cancer (TNBC) tumors compared with luminal A and luminal B tumors. Furthermore, having one C allele in the rs1412125 domain increased the risk of pathologic grade 3 disease in HER2-enriched and TNBC tumors. Our results indicate that genetic variations in the HMGB1 gene may serve as an important predictor of breast cancer progression and metastasis.

Translational opportunities for broad-spectrum natural phytochemicals and targeted agent combinations in breast cancer

Breast cancer (BC) prevention and therapy in the context of life-style risk factors and biological drivers is a major focus of developmental therapeutics in oncology. Obesity, alcohol, chronic estrogen signaling and smoking have distinct BC precipitating and facilitating effects that may act alone or in combination. A spectrum of signaling events including enhanced oxidative stress and changes in estrogen-receptor (ER)-dependent and -independent signaling drive the progression of BC. Breast tumors modulate ERα/ERβ ratio, upregulate proliferative pathways driven by ERα and HER2 with a parallel loss and/or downregulation of tumor suppressors such as TP53 and PTEN which together impact the efficacy of therapeutic strategies and frequently lead to emergence of drug resistance. Natural phytochemicals modulate oxidative stress, leptin, integrin, HER2, MAPK, ERK, Wnt/β-catenin and NFκB signaling along with regulating ERα and ERβ, thereby presenting unique opportunities for both primary and combinatorial interventions in BC. In this regard, this article focuses on critical analyses of the evidence from multiple studies on the efficacy of natural phytochemicals in BC. In addition, areas in which the combinations of such effective natural phytochemicals with approved and/or developing anticancer agents can be translationally beneficial are discussed to derive evidence-based inference for addressing challenges in BC control and therapy.

FSCN1 gene polymorphisms: biomarkers for the development and progression of breast cancer

Breast cancer is a major cause of cancer mortality worldwide. Fascin-1 (FSCN1) is an actin-binding protein found in mammalian cells, including endothelial, neuronal and mesenchymal cells. FSCN1 overexpression has been indicated in breast cancer patients. However, scant information is available regarding the association between FSCN1 single nucleotide polymorphisms (SNPs) and the risk or prognosis of breast cancer. We report on the association between 6 SNPs of the FSCN1 gene (rs56156320, rs8772, rs3801004, rs2966447, rs852479 and rs1640233) and breast cancer susceptibility as well as clinical outcomes in 316 patients with breast cancer and in 222 healthy controls. Carriers of the AC or AC + CC allele of the variant rs56156320 were at greater risk of breast cancer compared with wild-type (AA) carriers. Moreover, carriers of at least one G allele in rs3801004 were likely to progress to stage III/IV disease and lymph node metastasis. Individuals with at least one T allele at FSCN1 SNP rs2966447 were at higher risk of developing pathologic grade G3 disease. Furthermore, individuals bearing the C/C haplotype at SNPs rs56156320 and rs3801004 had nearly twice the risk of breast cancer. Our results indicate that genetic variations in the FSCN1 gene may serve as an important predictor of early-stage breast cancer.

An interaction network approach to study the correlation between endocrine disrupting chemicals and breast cancer

Endocrine disrupting chemicals (EDCs) are natural or synthetic exogenous substances affecting human health. Although present at low concentrations in the environment, they can cause a broad range of negative effects on the endocrine functions by mimicking the action of steroid hormones due to their structural similarity. Hormonal unbalance can play an important role in carcinogenesis at any stage of disease. In the case of the breast cancer, EDCs directly affect the transformation of normal breast cells into cancer cells by interfering with hormonal regulation and by inducing the alteration of factors that regulate gene expression. The principal aims of this work were to study the interaction networks of proteins modulated in breast cancer by either environmental EDCs or mycotoxins, and to identify the proteins with the strongest coordination role defined as hub nodes. Our studies evidenced the presence of seven and six hub proteins in two EDCs and mycotoxins networks, respectively. Then, by merging the two networks, we identified that three hub nodes (BCL2, ESR2 and CTNNB1) in the environmental EDCs network show direct interactions with three hub nodes (CASP8, RELA and MKI67) in the mycotoxins network. These data highlighted that two networks are linked through proteins involved in the apoptosis regulation and in processes related to cell proliferation and survival, and, thus, in breast cancer progression.

Tumor-Associated Mutations in Caspase-6 Negatively Impact Catalytic Efficiency

Unregulated, particularly suppressed programmed cell death is one of the distinguishing features of many cancer cells. The cysteine protease caspase-6, one of the executioners of apoptotic cell death, plays a crucial role in regulation of apoptosis. Several somatic mutations in the CASP6 gene in tumor tissues have been reported. This work explores the effect of CASP6 tumor-associated mutations on the catalytic efficiency and structure of caspase-6. In general, these mutations showed decreased overall rates of catalytic turnover. Mutations within 8 Å of the substrate-binding pocket of caspase-6 were found to be the most catalytically deactivating. Notably, the R259H substitution decreased activity by 457-fold. This substitution disrupts the cation-π stacking interaction between Arg-259 and Trp-227, which is indispensable for proper assembly of the substrate-binding loops in caspase-6. Sequence conservation analysis at the homologous position across the caspase family suggests a role for this cation-π stacking in the catalytic function of caspases generally. These data suggest that caspase-6 deactivating mutations may contribute to multifactorial carcinogenic transformations.

Discovery of cancer common and specific driver gene sets

Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found.