A number of cancer research organisations target pancreatic cancer as it is one of the most difficult cancers to treat. No simple early detection method, multiple genetic alterations in tumour cells and limited ability for drugs to reach the tumour provide serious obstacles to viable therapeutic solutions and diagnostics. The Biophysical Cancer Research Foundation hopes that its GGF technology might provide new insights to this intractable problem as explained below. An example of how one leading research institute is tackling Pancreatic cancer involves a new clinical trial.

Project leader, the Garvan Institute stated in their media release (26.2.2021)  : “A national clinical trial program will test promising new targeted therapy for pancreatic cancer, one of the deadliest forms of cancers of which more than 3000 cases are diagnosed annually in Australia alone.

The clinical trial program (MoST–P), led by researchers and clinicians at UNSW Sydney and the Garvan Institute of Medical Research, will provide patients with access to either targeted therapies matched to the genomic signature of their individual tumour, or targeted to the tumour environment.”

GGF potential contribution

The public statements included reference to scar tissue changing its behaviour in the presence of the pancreatic tumour. If the scar tissue changes are caused by genomic changes in the scar tissue cells genomic analysis such as NGS sequencing may provide insights to formulate typical genomic sequences encoding the etiology of the scar tissue. However, statistical analysis may be challenging to identify typical patterns across the genome due to the expected ‘noise’ across intergenic regions etc. GGF Geneseeker software suite developed in conjunction with Mathematica consultants in 2020 can provide advanced analysis of genomes especially across intergenic regions with minimal ‘noise’ due to the meaningful results to date from many genomes. Each ‘run’ of the Geneseeker software produces up to 15 frameshift images for comparison,  both 2D superimposition and 3D mesh modelling and other modelling. These may assist in developing generic motifs of cells in tissue surrounding tumours. Moreover, if it appears that the tumour is spreading its own ‘antigens’ (such as aberrant proteins leaking from tumours) which reach the surrounding tissues. The GGF Codeweaver algorithm could also be enlisted to develop GGF Peptides as candidate ligands to inhibit such ‘antigens’ and encoded or packaged in delivery vectors as medication for scar tissue to limit spread of the tumour or metastases . Already companies are developing small molecule drugs to recruit ubiquitin ligases to dock onto and inhibit ‘antigens’ such as these aberrant proteins leaking from tumours.