We analyze the expression of over 15,000 protein-coding genes and microRNA sequences to construct a map of the intracellular signaling pathways affected by an individual patient’s cancer.

Research Method

Our method is based on personalized profiling of malignant tissue transcriptomes versus a complementary set of healthy, normally functioning tissues, where the transcriptome is defined as the entire set of transcribed RNA molecules, which either transmit genetic information from DNA (genes) to functional proteins (mRNAs) or influence activity of protein-encoding mRNAs (microRNAs).

Although knowing aberrations in certain genes commonly mutated in cancer may be helpful to study familial disorders or to roughly predict sensitivity of certain cancers to targeted therapies, molecular profiling of the activity of the entire genome (i.e. transcriptome) is much more comprehensive and informative and has been established to have a far superior predictive value in the modern molecular medicine compared to the analysis if individual genetic alterations.

 

This may be partly explained by the fact that there are two copies of DNA in the human genome, meaning that active mutations or substitutions in one of the copies may be masked by the other, also active, yet non-mutated copy of DNA. The protein produced from the non-mutated gene sequence can sometimes mask the abnormal protein produced from an almost identical, yet mutated gene sequence.

Additionally, cancer cells experience a constant mutational pressure, which is another significant concern of genomic DNA-based predictions. The constantly changing mutational status of cancerous cells is mostly due to deregulation or even cancellation of fundamental DNA repair systems, which are in charge of the integrity and stability of a properly functioning cellular genome. When the cell is short of DNA repair mechanisms, it accumulates mutations very quickly, but only a minor fraction of these mutations can produce a significant physiological effect that would lead to the cancerous cell transformation.

In other words, finding the few so-called “driver” mutations, which are the most important and physiologically-relevant ones, among the huge number of “passenger” mutations that do not influence cancer phenotype, is similar to searching for a needle in a haystack. It may take too much time and turn out to be too expensive to identify which particular mutation is “the guilty party” for cancer progression in an individual patient.

 

In addition, and more importantly, this information in the majority of cases cannot help treat the patient. Simply knowing the causative mutations cannot invent a drug for the patient that will reverse the mutational process or annihilate the mutations’ effects.

 

Based on these theoretical considerations and on our extensive practical experience in both fundamental and applied biomedicine, along with a thorough analysis of the plethora of clinical reports on cancer and its genetic drivers, we have created a unique platform termed OncoFinder to analyze a patient’s transcriptome for optimization of his/her anticancer therapy.

For each patient, we analyze the expression of over 15,000 protein-coding genes and microRNA sequences to construct a map of the intracellular signaling pathways affected in an individual patient’s cancer.  We then consider a comprehensive database of available anticancer drugs and bioinformatically identify those targeted therapeutics that are predicted to kill cancer cells most efficiently, while leaving the normal cells of the body minimally affected. OncoFinder is an innovative platform that is based on our original bio-mathematical algorithms, a portion of which we recently published in several academic research journals. These algorithms are presently available for free to the biomedical community. The mathematical basis of the OncoFinder technology is available online.

We believe that patients, doctors, and the entire community will greatly benefit from our approach, by significantly saving the time, money, and other resources necessary to find the most efficient cancer therapies quicker and more reliably than with other existing methods. Our research team provides every client with a detailed report of our findings, a comprehensive analysis of relevant clinical trial data, and a review of the current clinical and biomedical literature pertaining to his/her case. Each report lists both, commonly prescribed as well as alternative treatment options, and includes information on their predicted effectiveness for the particular patient’s case. Upon request, our team can also discuss the possibility of an extended study or a follow-up project for you.

 

To request the legal documentation required to access the OncoFinder software, please contact us

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