Multidrug resistance in solid tumours

Introduction: Most cancers show heterogeneity of response to chemotherapy. This may be due in part to the differential expression of drug resistance proteins and the molecular targets of the drugs concerned. Methods: An ex vivo ATP-based Tumour Chemosensitivity Assay (ATP-TCA), immunohistochemistry and quantitative RT-PCR have been used to assess the chemosensitivity and resistance of a variety of solid tumours and cell lines. Results: (a) Melanoma cell lines showed higher chemosensitivity than tumour-derived cells, partially reversible by lowering the serum concentration, and hence the proliferation rate of the cells. (b) Studies of retinoblastoma samples confirmed that this malignancy is susceptible to cytotoxic drugs of all types, though multidrug resistance may occur in some cases. (c) The ATP-TCA was used to study the activity of high-dose doxorubicin in combination with other cytotoxic agents in ovarian adenocarcinoma samples. The combination of liposomal doxorubicin + vinorelbine was selected for further development. (d) A number of experimental drugs with varying sensitivity to resistance mechanisms were also assessed. One drug, XR5944, has entered phase I/II clinical trials during the course of this project, and the data have provided clinical indications. (e) An inhibitor of multi-drug resistance, tariquidar, has been tested in combination with doxorubicin, vinorelbine or paclitaxel, and has been shown to reverse this resistance. (f) Molecular studies have determined the expression of topoisomerases and drug transporters in tumour cells before and after exposure to chemotherapeutic agents. P-gp expression has been found to be a determinant of sensitivity to a certain number of drugs. Conclusion: The results suggest that drug resistance contributes to heterogeneity of chemosensitivity in many solid tumour types, as well as other mechanisms. Reversal of such resistance may benefit a subset of patients undergoing chemotherapy

PO-332 Genomic landscapes, neoantigen profiles and biological impact of MLH1 inactivation in cancer cells

Introduction Alterations in DNA repair pathways are thought to fuel tumour progression. Mismatch Repair (MMR) deficient cancers show peculiar biological features such as an indolent progression and a resolute therapeutic response to checkpoint inhibitors. The genomic and biological bases of the peculiar clinical features are poorly understood. Further progress in this area is limited by the paucity of models to study the impact of MMR genes inactivation at the genomic and biological levels. To address this issue we developed a bioinformatic workflow to monitor the neoantigen repertoire induced by inactivation of the Mlh1 gene (a key player of the MMR machinery), in murine cell lines. Material and methods We inactivated Mlh1 throughout the CRISPR-Cas9 technology in CT26 (colon cancer), PDAC (pancreatic cancer) and TSA (breast cancer) murine cell lines. We performed whole exome sequencing (WES) at different time points and then we quantified the amount of mutations (SNVs and indels). We generated a pipeline that characterises the neoantigen repertoire, starting from annotated alterations and the HLA of specific murine strain. In parallel, we inoculated MMR-proficient and -deficient cells in immuno-compromised and -competent mice and monitored their growth. Results and discussions In all pre-clinical models analysed we found a massive increment in the number of non-synonymous alterations (up to 100% increase respect to basal population) after Mlh1 inactivation. Notably, analysis of MMR deficient mouse cells at different time points showed a renewal of mutational profile and consequently an accumulation of predicted neoantigens. We further characterised the SNVs and frameshifts acquired by Mlh1-knockout cells. In agreement with data in human tumours, the fraction of predicted neoantigens derived from frameshifts was higher than the SNV-derived neoantigens. When injected in immuno-compromised mice the Mlh1-knockout cells and their wild type counterpart showed comparable growth. On the contrary, MMR-deficient cells but not their control counterpart grew poorly in immuno-competent mice and responded promptly to treatment with checkpoint inhibitors. Conclusion We find that Mlh1 gene inactivation drives dynamic neoantigen profiles, which can be monitored with an ad hoc bioinformatic pipeline. These analyses provide mechanistic support to understand why MMR deficient cells engage the immune system of the host, foster immune surveillance and tumour control

Reply: KRAS status analysis and anti-EGFR therapies: is comprehensiveness a biologist's fancy or a clinical necessity?

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