scholarly journals Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kalifa Manjang ◽  
Shailesh Tripathi ◽  
Olli Yli-Harja ◽  
Matthias Dehmer ◽  
Galina Glazko ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Progression ◽  
Disease Etiology ◽  
Signature Genes ◽  
Biological Meaning ◽  
Gene Sets ◽  
Breast Cancer Outcome ◽  
Biological Interpretation ◽  
Pathological Behavior

AbstractThe identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.

IS tRNA DRIVING BREAST CANCER PROGRESSION?

2019 ◽  
Author(s):  
Zil-e- Rubab
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Developing Countries ◽  
Molecular Mechanism ◽  
Cancer Progression ◽  
Critical Review ◽  
Driving Forces ◽  
Treatment Modalities ◽  
Critical Research ◽  
Research Article

This critical research periodical is mainly based on critical review of research article titled ‘Modulated Expression of Specific tRNAs Drives Gene Expression and Cancer Progression published in Cell by Goodarzi et al1. According to Globocan, 2008 report2, breast is among the leading site of new cancer cases and deaths (691,300/268,900) in females of developing countries and second leading site in USA (Globocan, 2012)3. The extensive research is in progress on different aspects of molecular mechanism of driving forces and different treatment modalities to ease this burden. The above mentioned research article is also part of this effort.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer

2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Therapy ◽  
Cancer Treatment ◽  
Cancer Survival ◽  
Expression Profiles ◽  
Functional Gene ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
Gene Sets

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.

scholarly journals Intratumoral Adipocyte-High Breast Cancer Enrich for Metastatic and Inflammation-Related Pathways but Associated with Less Cancer Cell Proliferation

2020 ◽  
Vol 21 (16) ◽  
pp. 5744 ◽  
Author(s):  
Yoshihisa Tokumaru ◽  
Masanori Oshi ◽  
Eriko Katsuta ◽  
Li Yan ◽  
Jing Li Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Proliferation ◽  
Cancer Progression ◽  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Related Gene ◽  
Immune Microenvironment ◽  
Gene Sets ◽  
Tumor Immune Microenvironment ◽  
Er Positive

Cancer-associated adipocytes are known to cause inflammation, leading to cancer progression and metastasis. The clinicopathological and transcriptomic data from 2256 patients with breast cancer were obtained based on three cohorts: The Cancer Genome Atlas (TCGA), GSE25066, and a study by Yau et al. For the current study, we defined the adipocyte, which is calculated by utilizing a computational algorithm, xCell, as “intratumoral adipocyte”. These intratumoral adipocytes appropriately reflected mature adipocytes in a bulk tumor. The amount of intratumoral adipocytes demonstrated no relationship with survival. Intratumoral adipocyte-high tumors significantly enriched for metastasis and inflammation-related gene sets and are associated with a favorable tumor immune microenvironment, especially in the ER+/HER2- subtype. On the other hand, intratumoral adipocyte-low tumors significantly enriched for cell cycle and cell proliferation-related gene sets. Correspondingly, intratumoral adipocyte-low tumors are associated with advanced pathological grades and inversely correlated with MKI67 expression. In conclusion, a high amount of intratumoral adipocytes in breast cancer was associated with inflammation, metastatic pathways, cancer stemness, and favorable tumor immune microenvironment. However, a low amount of adipocytes was associated with a highly proliferative tumor in ER-positive breast cancer. This cancer biology may explain the reason why patient survival did not differ by the amount of adipocytes.

Molecular characteristics and metastasis predictor genes of triple-negative breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1043-1043
Author(s):  
Wen-Hung Kuo ◽  
Yao-Yin Chang ◽  
Ming-Feng Hou ◽  
Eric Y Chuang ◽  
King-Jen Chang
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Early Stage ◽  
Gene Signature ◽  
Breast Cancers ◽  
Prognostic Signature ◽  
Characteristic Analysis ◽  
Disease Etiology ◽  
Breast Cancer Outcome

1043 Background: Triple-negative breast cancer(TNBC) is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible. Methods: Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated with oligonucleotide microarrays. A prognostic 45-gene signature for triple-negative breast cancer was identified using Student’s t test and receiver operating characteristic analysis. Results: Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A novel 45-gene signature giving 98% predictive accuracy in distant metastasis recurrence was identified in our triple-negative patient cohort. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% CI 1.04-5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The prognostic signature was statistically predictive with the node-negative triple-negative patients in the validation cohort. Conclusions: The 45-gene prognostic signature identified in this study revealed that TGF-β signaling in immune/inflammatory regulation may be critically involved in distant metastatic invasion of TNBC. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of metastasis recurrence for early-stage triple-negative patients.

Osteopontin induces multiple changes in gene expression that reflect the six “hallmarks of cancer” in a model of breast cancer progression

2005 ◽  
Vol 43 (4) ◽  
pp. 225-236 ◽  
Author(s):  
Amy C. Cook ◽  
Alan B. Tuck ◽  
Susan McCarthy ◽  
Joel G. Turner ◽  
Rosalyn B. Irby ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Progression ◽  
Breast Cancer Progression ◽  
Hallmarks Of Cancer
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