Elucidating feed‑forward apoptosis signatures in breast cancer datasets: Higher FOS expression associated with a better outcome

Abstract

Overstimulation of pro-proliferative pathways and high level expression of pro-proliferative transcription factors (TFs) can lead to apoptosis. This is likely due to TF binding sites for pro-proliferative TFs common to pro-proliferative and pro-apoptosis-effector genes. Certain clinical datasets have indicated that molecular markers associated with higher proliferation rates lead to improved outcomes for patients with cancer. These observations have been extensively assessed on a general basis, however there has been little work dissecting feed-forward apoptosis signaling pathways that may represent specific distinctions between a pro-proliferative mechanism and a pro-apoptotic mechanism in samples from patients with cancer. Using The Cancer Genome Atlas datasets and bioinformatic approaches, the present study reports that higher FOS expression levels, along with higher FOS target apoptosis-effector gene expression, is associated with an increased survival, while higher POU2F1 expression is associated with a reduced survival (average difference of 25.9 months survival). In summary, in the datasets examined FOS represents an apoptosis-driver and high POU2F1 represents a driver mechanism for cancer development.

The miR-370/UQCRC2 axis facilitates tumorigenesis by regulating epithelial-mesenchymal transition in Gastric Cancer

“…UQCRC2 is a mitochondrial respiratory complex III subunit that is up-regulated in colorectal cancer and can accelerate its proliferation and metastasis 5 . Meanwhile, UQCRC2 levels are reported to be altered in many cancers, including testicular cancer and breast cancer 15 - 17 . However, the role of UQCRC2 and specific miRNAs in the development of GC remains unclear.…”

Transcription Factor Profiling to Predict Recurrence-Free Survival in Breast Cancer: Development and Validation of a Nomogram to Optimize Clinical Management

“…For instance, HDAC2 overexpression has been associated with aggressive clinicopathological features and the DDR pathway in BC (Shan et al, 2017). Moreover, a study found that high SMARCA4 or SMARCA2 expression is frequently associated with opposite prognoses in BC (Guerrero-Martinez and Reyes, 2018), while high FOS expression has been associated with better BC prognosis (Fisler et al, 2018). Due to the different screening pipelines, there is no significant correlation between the three hub genes and the above nine predictive TFs.…”

An age-based, RNA expression paradigm for survival biomarker identification for pediatric neuroblastoma and acute lymphoblastic leukemia

“…Second, it is clear that many cancer hallmarks are dependent on signal pathway amplification rather than a molecular on/off switch. This is exemplified by feed forward apoptosis, whereby transcription factors that activate pro-proliferative genes, such as histone genes, also activate apoptosis-effector genes, i.e., when these transcription factors are expressed at high levels [8–10, 38–42]. Third, even outside of the cancer setting, different tissues can have opposite functions for the same signaling pathway; FGFR3 activating mutations stimulate spermatocyte cell division but inhibit chondrocyte cell division, leading to achondroplasia [43, 44].…”

“…Keeping in mind that many gene expression scenarios, particularly associated with development [6, 7], involve a gradient of expression and signal pathway activation gradients, and that signal pathway activation gradients have also been reported to represent distinct outputs in the cancer setting [8–10], we took an approach to biomarker discovery for NBL and ALL that emphasized a continuum of expression levels, with the expectation that, for certain genes, the higher the expression level, the greater the probability of a discreet effect, in this case a discreet effect leading to a survival distinction. Thus, in this study, we used RNA expression data from the TARGET database to first identify genes whereby a continuum of expression could be established as having a correlation with age, and then to additionally, independently filter such genes for an association of expression levels with distinct survival rates.…”