Novel therapeutic approaches are required to treat ovarian cancer and dependency on glycolysis may provide new targets for treatment. This study sought to investigate the variation of expression of molecular components (GLUT1, HKII, PKM2, LDHA) of the glycolytic pathway in ovarian cancers and the effectiveness of targeting this pathway in ovarian cancer cell lines with inhibitors. Expression of GLUT1, HKII, PKM2, LDHA were analysed by quantitative immunofluorescence in a tissue microarray (TMA) analysis of 380 ovarian cancers and associations with clinicopathological features were sought. The effect of glycolysis pathway inhibitors on the growth of a panel of ovarian cancer cell lines was assessed by use of the SRB proliferation assay. Combination studies were undertaken combining these inhibitors with cytotoxic agents. Mean expression levels of GLUT1 and HKII were higher in high grade serous ovarian cancer (HGSOC), the most frequently occurring subtype, than in non-HGSOC. GLUT1 expression was also significantly higher in advanced stage (III/IV) ovarian cancer than early stage (I/II) disease. Growth dependency of ovarian cancer cells on glucose was demonstrated in a panel of ovarian cancer cell lines. Inhibitors of the glycolytic pathway (STF31, IOM-1190, 3PO and oxamic acid) attenuated cell proliferation in platinum-sensitive and platinum-resistant HGSOC cell line models in a concentration dependent manner. In combination with either cisplatin or paclitaxel, 3PO (a novel PFKFB3 inhibitor) enhanced the cytotoxic effect in both platinum sensitive and platinum resistant ovarian cancer cells. Furthermore, synergy was identified between STF31 (a novel GLUT1 inhibitor) or oxamic acid (an LDH inhibitor) when combined with metformin, an inhibitor of oxidative phosphorylation, resulting in marked inhibition of ovarian cancer cell growth. The findings of this study provide further support for targeting the glycolytic pathway in ovarian cancer and several useful combinations were identified.

Radiotherapy plays an important role in the multimodal treatment of breast cancer. The response of a breast tumour to radiation depends not only on its innate radiosensitivity but also on tumour repopulation by cells that have developed radioresistance. Development of effective cancer treatments will require further molecular dissection of the processes that contribute to resistance. Radioresistant cell lines were established by exposing MDA-MB-231, MCF-7 and ZR-751 parental cells to increasing weekly doses of radiation. The development of radioresistance was evaluated through proliferation and colony formation assays. Phenotypic characterisation included migration and invasion assays and immunohistochemistry. Transcriptomic data were also generated for preliminary hypothesis generation involving pathway-focused analyses. Proliferation and colony formation assays confirmed radioresistance. Radioresistant cells exhibited enhanced migration and invasion, with evidence of epithelial-to-mesenchymal-transition. Significantly, acquisition of radioresistance in MCF-7 and ZR-751 cell lines resulted in a loss of expression of both ERα and PgR and an increase in EGFR expression; based on transcriptomic data they changed subtype classification from their parental luminal A to HER2-overexpressing (MCF-7 RR) and normal-like (ZR-751 RR) subtypes, indicating the extent of phenotypic changes and cellular plasticity involved in this process. Radioresistant cell lines derived from ER+ cells also showed a shift from ER to EGFR signalling pathways with increased MAPK and PI3K activity. This is the first study to date that extensively describes the development and characterisation of three novel radioresistant breast cancer cell lines through both genetic and phenotypic analysis. More changes were identified between parental cells and their radioresistant derivatives in the ER+ (MCF-7 and ZR-751) compared with the ER- cell line (MDA-MB-231) model; however, multiple and likely interrelated mechanisms were identified that may contribute to the development of acquired resistance to radiotherapy.

Background: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated. Methods: This study describes our experiences of nine new and established mRNA profiling techniques including Lexogen QuantSeq, Qiagen QiaSeq, BioSpyder TempO-Seq, Ion AmpliSeq, Nanostring, Affymetrix Clariom S or U133A, Illumina BeadChip and RNA-seq of formalin-fixed paraffin embedded (FFPE) and fresh frozen (FF) sequential patient-matched breast tumour samples. Results: The number of genes represented and reliability varied between the platforms, but overall all methods provided data which were largely comparable. Crucially we found that it is possible to integrate data for combined analyses across FFPE/FF and platforms using established batch correction methods as required to increase cohort sizes. However, some platforms appear to be better suited to FFPE samples, particularly archival material. Conclusions: Overall, we illustrate that technology selection is a balance between required resolution, sample quality, availability and cost.

Tumour budding (TB), lymphatic vessel density (LVD) and lymphatic vessel invasion (LVI) have shown promise as prognostic factors in colorectal cancer (CRC) but reproducibility using conventional histopathology is challenging. We demonstrate image analysis methodology to quantify the histopathological features which could permit standardisation across institutes and aid risk stratification of Dukes B patients.

Treatment for HR+/HER2+ patients has been debated, as some tumors within this luminal HER2+ subtype behave like luminal A cancers, whereas others behave like non-luminal HER2+ breast cancers. Recen... Lay abstract About 10% of all breast cancer tumors are both HR+ and HER2+. It is clear that some patients with this type of breast cancer will require only hormone therapy aimed at HRs and others w...

Neoadjuvant chemotherapy is increasingly given preoperatively to shrink breast tumours prior to surgery. This approach also provides the opportunity to study the molecular changes associated with treatment and evaluate whether on-treatment sequential samples can improve response and outcome predictions over diagnostic or excision samples alone. This study included a total of 97 samples from a cohort of 50 women (aged 29–76, with 46% ER+ and 20% HER2+ tumours) with primary operable breast cancer who had been treated with neoadjuvant chemotherapy. Biopsies were taken at diagnosis, at 2 weeks on-treatment, mid-chemotherapy, and at resection. Fresh frozen samples were sequenced with Ion AmpliSeq Transcriptome yielding expression values for 12,635 genes. Differential expression analysis was performed across 16 patients with a complete pathological response (pCR) and 34 non-pCR patients, and over treatment time to identify significantly differentially expressed genes, pathways, and markers indicative of response status. Prediction accuracy was compared with estimations of established gene signatures, for this dataset and validated using data from the I-SPY 1 Trial. Although changes upon treatment are largely similar between the two cohorts, very few genes were found to be consistently different between responders and non-responders, making the prediction of response difficult. AAGAB was identified as a novel potential on-treatment biomarker for pathological complete response, with an accuracy of 100% in the NEO training dataset and 78% accuracy in the I-SPY 1 testing dataset. AAGAB levels on-treatment were also significantly predictive of outcome (p = 0.048, p = 0.0036) in both cohorts. This single gene on-treatment biomarker had greater predictive accuracy than established prognostic tests, Mammaprint and PAM50 risk of recurrence score, although interestingly, both of these latter tests performed better in the on-treatment rather than the accepted pre-treatment setting. Changes in gene expression measured in sequential samples from breast cancer patients receiving neoadjuvant chemotherapy resulted in the identification of a potentially novel on-treatment biomarker and suggest that established prognostic tests may have greater prediction accuracy on than before treatment. These results support the potential use and further evaluation of on-treatment testing in breast cancer to improve the accuracy of tumour response prediction.