Title : Combinational in silico methods-based screening and selection of druggable targets in certain immune, non-immune and stromal cells in TNBC TME - Lessons for delivery of natural molecules with differentiation potential
Abstract:
Based on existing diagnostic data, Breast Cancer (BC) stands second globally and is also a significant contributor to cancer-related deaths in women1 in several countries including India, necessitating research endeavours in terms of identifying mechanistically relevant targets and drugs that can eliminate these cancerous cells2. Triple-Negative Breast Cancer (TNBC) represents a significant heterogeneous subset of BC (15% to 25%) and is characterized by its aggressive behaviour and invasive potential, attributable, in major part, to variations in the Tumour Microenvironment (TME)3. Also, the inherent heterogeneity and the consequent variations in the TME (in terms of the varying stoichiometries of the respective cell types and the soluble factors in the local milieu) as well as the consequent alterations in the inter-individual drug response are fairly well documented, thereby warranting a need to develop integrated approaches and improved methods for disease classification using the different existing datasets and classification strategies. This methodology can possibly provide a road map for developing and/or refining drug regimens4. Among the different strategies, pro-differentiation therapy can be considered to a promising approach with considerable potential in TNBC therapy. In this regard, we have shown (using a combination of in silico approaches) that natural molecules have good binding behaviour to certain proteins that are part of the prolactin-based differentiation pathway5. In this regard, the major cellular targets in the TME milieu that present opportunities for drugs with pro-differentiation potential include the cancer stem cells, epithelial cells that have undergone EMT, myeloid cells that can skew macrophage cell types to more of the pro-inflammatory M1 lineage, as well as target CAFs, since they support the de-differentiated status in other cell types6. In this regard, targets that are representative of the heterogeneous TME in the aforesaid key cell types will be identified, including isoforms of certain proteins (for e.g., those belonging to the STAT family), for the possible induction of the differentiated cells7, based on PPI networks created and verified using multiple approaches including literature-based searches. A combination of in silico tools will be used to screen chemical libraries (for e.g., COCONUT8) and repositioned drugs for identifying the best ligand-target combination by ranking the respective binding affinities, thereby providing opportunities for evaluating the possibility of dual targeting (for e.g., possibly inducing STAT1 homodimers as well as modulating STAT5 levels). In this regard, the STAT5 canonical homodimer upregulation is necessary for the non-malignant macrophage phenotype9 as opposed to the aberrant tetramer’s role in non-canonical gene expression linked with tumour progression). This selection can provide opportunities for improvements in the selectivity of drug action by making structural refinements and/or improve bioavailability using liposome-based delivery strategies for combination therapy10. Such methods can synergise with therapeutic modalities that employ ICI inhibitors11 as drugs of immunotherapeutic potential.
