About this Research Topic
Although diagnosis and treatment of various cancer types have made significant strides recently, drug resistance is a major challenge faced in the cancer clinic. Cancer cells evolve continuously through a combination of genetic mutations, epigenetic changes, support from cellular and acellular tumour microenvironment. The chemoresistant tumour cells expand and become the dominant population and, at this point, it becomes difficult to treat. The cancer cell heterogeneity is also a major contributing factor to chemoresistance. The other challenge faced is the development of adverse events due to drug toxicity which is overwhelming especially for immunocompromised patients. Collectively, these factors reduce the treatment response and overall survival.
Current neoadjuvant chemotherapy (NACT) and targeted therapies aim at drug efficacy with minimal toxicity along with employment of adjuvant immunotherapy. Potential exploits include novel drug delivery platforms such as antibody-drug conjugates, combination therapies that target addicted signalling pathways, transcription factors, utilization of long noncoding RNAs including siRNA and miRNA using nanocarriers, reprogramming the tumour immune microenvironment (TIME), employment of in silico approaches from docking drug-like molecules to crystal structures of novel targets, bioinformatics, and machine learning approaches. These approaches hold immense potential to enhance cancer therapeutics while minimizing toxicities. These strategies aim to amplify therapy impact while minimizing toxicity leading to better patient outcome.
This research topic welcomes data and review articles on the following sub-topics but are not limited to:
1. Novel molecular targets, targeting of signalling pathways, transcription, and epigenetic factors, proteomic, metabolomic and single-cell analyses of therapy-naïve and chemoresistant tumour cell populations.
2. Role of non-coding RNAs and microRNAs in chemoresistance.
3. Advancements in tumour immune microenvironment (TIME) and therapies taking advantage of reprogramming the TIME.
3. Novel synthetic and natural-derived compounds for targeted therapy to improve anti-cancer efficacy, overcoming resistance and minimizing toxicities.
4. Cancer stem or stem-like cells in creation of minimal residual disease and induction of drug resistance, cancer stemness factors that induce and orchestrate chemoresistance.
5. Bioinformatics, in silico studies and machine learning in design for the study of novel molecules to enhance efficacy and overcome resistance to anticancer drugs and toxicities. In silico results should be validated through the exploitation of experimental methodologies.
Current neoadjuvant chemotherapy (NACT) and targeted therapies aim at drug efficacy with minimal toxicity along with employment of adjuvant immunotherapy. Potential exploits include novel drug delivery platforms such as antibody-drug conjugates, combination therapies that target addicted signalling pathways, transcription factors, utilization of long noncoding RNAs including siRNA and miRNA using nanocarriers, reprogramming the tumour immune microenvironment (TIME), employment of in silico approaches from docking drug-like molecules to crystal structures of novel targets, bioinformatics, and machine learning approaches. These approaches hold immense potential to enhance cancer therapeutics while minimizing toxicities. These strategies aim to amplify therapy impact while minimizing toxicity leading to better patient outcome.
This research topic welcomes data and review articles on the following sub-topics but are not limited to:
1. Novel molecular targets, targeting of signalling pathways, transcription, and epigenetic factors, proteomic, metabolomic and single-cell analyses of therapy-naïve and chemoresistant tumour cell populations.
2. Role of non-coding RNAs and microRNAs in chemoresistance.
3. Advancements in tumour immune microenvironment (TIME) and therapies taking advantage of reprogramming the TIME.
3. Novel synthetic and natural-derived compounds for targeted therapy to improve anti-cancer efficacy, overcoming resistance and minimizing toxicities.
4. Cancer stem or stem-like cells in creation of minimal residual disease and induction of drug resistance, cancer stemness factors that induce and orchestrate chemoresistance.
5. Bioinformatics, in silico studies and machine learning in design for the study of novel molecules to enhance efficacy and overcome resistance to anticancer drugs and toxicities. In silico results should be validated through the exploitation of experimental methodologies.
Keywords: Cancer; Signaling pathway; apoptosis; angiogenesis; drug repurposing; toxicity; resistance; biomarkers; chemotherapy; targeted therapy; survival; mortality; adverse events; mechanism; interaction; miRNA;
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
