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Cancer Therapies - Coggle Diagram

- - - - More recently this has been divided into ten different types
      - More simply divided into luminal A/B, Her2, basal and claudin low (Polyak. JCI, 2011)
        
        Of these claudin-low has the worst survival rate, with relapse-free survival at 0% after 150 months and the best outcomes seen in luminal A which has a RFS of ~80% at 200 months (the others are all 30-40%
      - TNBC are un-differentiated with a high frquency of p53 mutations and BRCA1 tumours often fall into this group but driver oncogenes are poorly studied
      - BCL11A is one of the most commonly overexpressed TFs in basal breast cancer (compared to the others), just after FOXC1 and ELF5
        
        This is also upregulated in B-cell leukaemia and is essential for lymphoid development and switch fetal-->adult haemoglobin
        
        Identified by looking at METABRIC and TCGA studies (Khaled, 2015)
        
        Correlated with other breast cancers (10-29%) but 67% of basal tumours express it (overexpression in ~20% METABRIC and ~40% TCGA data sets)
        
        Expression is driven by a lack of methylation (~20% of full methylation)
        
        KD reduces tumour burden in vitro using shRNA (to minimal levels in 4T1 and SUM159 but only about 50% in MDA231)
        
        DMBA induced tumours require BCL11A overexpression for tumours to properly grow (removing it prevents ~90% of test subjects getting infected) and losing p53 cannot overcome BCL11A loss
      - Was initially thought that BRCA1 tumours came from basal cells as they had basal gene expression signatures
        
        However Molyneux (2010) showed that BRCA1 + p53 deletion targeted to stem cells did not produce typical BRCA1-tumours but when targeted to progenitor cells it did
        
        Is now thought that claudin-like cancers are from stem cells, basal-like from priogenitor (bipotent, myoepithelial or luminal), HER2 are from late luminal progenitors and luminal cancers from differentiated myoepithelial and luminal cells (Prat & Perou, Nature Medicine, 2009)
  - - - Arises from therapy (Poulikakos, Cancer Cell, 2012)
    - - This paper shows a 'family tree' of mutations, suggesting that we should target the 'trunk' mutations - but these are not easy to target
      - Zhang's 2014 paper was done in lung cancer and demonstrated how poor our targeted approaches can be
  - - - Gupta (2009, Cell) identifies some selective inhibitors or cancer stem cells
        
        Same paper shows the issues of CSC/TICs in that they are highly resistance to cytotoxic substances
        
        Salinomycin is highlighted as being very effective in pushing cell viability downwards and was easy to reclassify (from being an antibiotic)
        
        Salinomycin also reduces the 'stemness' of a cell by reducing [CD44] and increasing [CD24]
        
        Has not been approved for use and does not seem to be being actively researched
- - - - Oncogenes are activated by:
        Chromosome rearrangement (MYC translocations in lympmhoma)
        Point mutations (KRAS in lung cancer and BRAF in melanoma)
        Gene amplification (HER2 in breast cancer - more than 6 copies)
        miRNA upregulation (not well studied due to previous thinking that they were inert) (Lujambio and Lowe,2012, Nature)
        
        miRNA-21 induces pre-B-cell lymphoma in the lymphnode, thymus and spleen (Medina, Nature, 2010) and it is thought to be due to its multiple targets - the concept of "OncomiR addiction" suggests that inhibiting miRNAs like this a broad range of cancers can be successfully treated
    - - Typically p53 activates MDM2, which then inhibits it
      - Responds to DNA damage/stress
      - Induces senescence, apoptosis, growth arrest and DNA repair
      - Heterozygous mutations are sufficient for cancerous
- - - - Tumour is excised and T cells are selected to target them, amplified and then put back in the patient (Rosenbery & Restifo, Science, 2015)
      - Chimeric antigen receptors can be developed by infecting T cells with a viral or non-viral receptor that is raised to the tumour cell
      - Relies on cell-surface expression from the tumour
    - - Mammaprint focuses on which therapy is post surgery (adjuvant therapy) and is common in the US, the UK is hoping to go for the whole genome sequencing first
        
        Genome analyses have shown good promise previously
        
        SAFIR01/UNICANCER trial found a targetable alteration in 46% of patients but only 13% could be offered a personalised therapy (SAFIR02 aims to improve upon this)
    - - Showed that two different BRAF inhibitors were more effective on cells with BRAF mutations (obviously), it also suggested some other correlations (NRAS increased sensitivity to both)
      - Nutlin3a resistance was shown to correlate with p53 mutations (unsurprising) but also BRAF and MYCN increased sensitivity (which was interesting)
      - Olaparib (PARPi) was shown to be especially effective on patients with EWS-FLI1 fusion mutations
        
        Further experiments showed that KD of the fusion protein resulted in resistance in cells that were previously sensitive to olaparib
      - Could be built upon with expression levels rather than just presence/absence of mutations
        Epigenetic data would also be useful to improve results and find more novel correlations
    - - Levels of CTCs (circulating tumour cells) are predictive of metastatic relapse (Keller & Pantel, 2019, Nature Rev Canc)
        
        This would be particularly useful for patients with a high chance of relapse therefore and liquid biopsies may make this easy for many patients (Dawson showed correlations in NEJM 2013 article)
      - Tumour biopsies could be used to determine:
        Which drugs to use (predictive)
        Who needs treatment (prognostic)
        What dosage to use (pharmacogenomic)
      - Genomic screens can be used to determine:
        I - the cancer drivers
        II - the resistant clones
        III - DNA repair defects (if BRCA is lost then PARPis can be used)
        IV - Charactise immune suppression mechanisms
        (Arnedos, 2015, Nature Rev Clin Onc)
    - - Drawback is cost
      - Can be used to test a few different drugs and look for biomarkers (Tentler, 2012, Nat Rev Clin Oncol)
      - (Gao, 2015, Nature Medicine) have shown how these can be used in clinical trial selection
      - Avatar mouse models allow 'mini-clinical trials' to be carried out using transgenic mice but is VERY VERY expensive so expectation is that it will only be used in high risk (in terms of relapse) patients
      - Genomics England are expected to deliver on this with the 100k genomes proect
      - Issues are:
        No protein-protein interactions can be looked at
        Large amounts of info
        Security concerns
        Ethical issues around ownership and should patients be told if AD or other drivers are found and they exhibit them?
  - - - T315I mutation is resistance to all major imatinib like drugs
      - Dasatinib is the most effective analogue (Milojkovic, 2009, Clin Cancer Res)
    - - Lumincal breast cancer is often (60-70%) caused by overactive ERalpha (binds ~14k sites in the genome - shown by ChIP, all called EREs)
        
        Tamoxifen is used to treat ERa overexpressing breast cancer and is one of the highest performing anti-cancer drugs (80% of patients survive after 5 years)
        
        Targets include cyclin D and MYC
      - HER2 over-expression is treated with herceptin - one of the first immunotherapies
        
        Nowadays often a cytotoxic payload is added to improve efficacy and cell-killing ability
    - - Cells with BRCA1/2 mutations can be killed with PARP inhibitors as inhibiting PARP causes single-stranded DNA breaks to form into double-stranded breaks (which cannot be fixed as BRCA is non-functional) (Underhill, 2011, Annals of Oncology)
        
        Have entered the clinic (Olaparib, Niraparib etc)
        
        However resistance has been seen in some cases as wt BRCA is reconstiuted in some cells
      - Some inital evidence was seen by Farmer's group in 2005 (Nature)
      - Other examples are STF-62247 (VHL) and CCI-779 (PTEN) for renal cancer (Chan & Giaccia, 2011, Nature Rev Drug Disc)
    - - Fusion occurs with genes like DotCom and SEC to cause overexpression of Wnt & leukaemic stem cell and HOX target genes respectively
      - I-BET is used to remove MLL machinery (Brd3/4) from binding histones (Dawson, 2011, Nature)
    - - Issues are typically that they are not selective enough and so have off-target effects
      - Adenoviruses produce E1B to suppress p53 and allow it to hijack the DNA machinery
        
        A mutant adenovirus was raised with a mutant E1B so that adenovirus can only replicate in cancerous cells that already have inactivated p53
    - - Monoclonal antibodies
        Immune adjuvants (BCG & imiquimod)
        Cytokines
        Supportive therapy (Leucovorin & G(M)-CSF)
        Prophylactic immune therapy (HPV & HBV vaccines)
        Bone marrow transplants
      - Can target PD1 as it is expressed on many cancer cells and blockade prevents the inhibition of T cells that results from it and subsequently stimulates an adaptive immune response (Tumeh, 2014, Nature)
        
        This requires T cells outside the tumour cell though (they need to be present and excluded from the tumour)
        
        Has also shown efficacy in metastatic bladder cancer which reinforces that accumulation of T cells just outside the tumour prior to therapy is necessary for therapy response