Inflammatory cytokines and aromatase inhibitor-associated musculoskeletal syndrome: a case–control study

The aromatase inhibitor (AI)-associated musculoskeletal syndrome (AIMSS) occurs in approximately 50% of AI-treated patients. Inflammatory mediators are associated with oestrogen signalling and may change with oestrogen depletion. We hypothesised that AIMSS may be associated with changes in circulating inflammatory markers

LMTK3 confers chemo-resistance in breast cancer

Lemur tyrosine kinase 3 (LMTK3) is an oncogenic kinase that is involved in different types of cancer (breast, lung, gastric, colorectal) and biological processes including proliferation, invasion, migration, chromatin remodeling as well as innate and acquired endocrine resistance. However, the role of LMTK3 in response to cytotoxic chemotherapy has not been investigated thus far. Using both 2D and 3D tissue culture models, we found that overexpression of LMTK3 decreased the sensitivity of breast cancer cell lines to cytotoxic (doxorubicin) treatment. In a mouse model we showed that ectopic overexpression of LMTK3 decreases the efficacy of doxorubicin in reducing tumor growth. Interestingly, breast cancer cells overexpressing LMTK3 delayed the generation of double strand breaks (DSBs) after exposure to doxorubicin, as measured by the formation of γH2AX foci. This effect was at least partly mediated by decreased activity of ataxia-telangiectasia mutated kinase (ATM) as indicated by its reduced phosphorylation levels. In addition, our RNA-seq analyses showed that doxorubicin differentially regulated the expression of over 700 genes depending on LMTK3 protein expression levels. Furthermore, these genes were found to promote DNA repair, cell viability and tumorigenesis processes / pathways in LMTK3-overexpressing MCF7 cells. In human cancers, immunohistochemistry staining of LMTK3 in pre- and postchemotherapy breast tumor pairs from four separate clinical cohorts revealed a significant increase of LMTK3 following both doxorubicin and docetaxel based chemotherapy. In aggregate, our findings show for the first time a contribution of LMTK3 in cytotoxic drug resistance in breast cancer

Serial analysis of circulating tumor cells in metastatic breast cancer receiving first-line chemotherapy

Background: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2,202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs (bCTC), combined CTC status at baseline to the end of cycle 1 (cCTC), and tCTC. Akaike Information Criterion (AIC) was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (tCTCneg, 56.9% ), low (tCTClo, 23.7%), intermediate (tCTCmid, 14.5%), or high (tCTChi, 4.9%). Patients with tCTClo, tCTCmid and tCTChi patterns had statistically significant inferior PFS and OS compared to those with tCTCneg (P<.001). AIC indicated that the tCTC model best predicted PFS and OS when compared to bCTC and cCTC models. Validation studies in an independent cohort of 1,856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified four novel prognostic groups in MBC based on similarities in CTC trajectory patterns during chemotherapy. Prognostic groups included patients with very poor outcome (tCTCmid+tCTChi, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be utilized for fine-tuning of CTC-based risk-stratification strategies to guide future prospective clinical trials in MBC

Serial Analysis of Circulating Tumor Cells in Metastatic Breast Cancer Receiving First-Line Chemotherapy

32siBackground: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9%), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P <. 001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC.reservedmixedMagbanua M.J.M.; Hendrix L.H.; Hyslop T.; Barry W.T.; Winer E.P.; Hudis C.; Toppmeyer D.; Carey L.A.; Partridge A.H.; Pierga J.-Y.; Fehm T.; Vidal-Martinez J.; Mavroudis D.; Garcia-Saenz J.A.; Stebbing J.; Gazzaniga P.; Manso L.; Zamarchi R.; Antelo M.L.; Mattos-Arruda L.D.; Generali D.; Caldas C.; Munzone E.; Dirix L.; Delson A.L.; Burstein H.J.; Qadir M.; Ma C.; Scott J.H.; Bidard F.-C.; Park J.W.; Rugo H.S.Magbanua, M. J. M.; Hendrix, L. H.; Hyslop, T.; Barry, W. T.; Winer, E. P.; Hudis, C.; Toppmeyer, D.; Carey, L. A.; Partridge, A. H.; Pierga, J. -Y.; Fehm, T.; Vidal-Martinez, J.; Mavroudis, D.; Garcia-Saenz, J. A.; Stebbing, J.; Gazzaniga, P.; Manso, L.; Zamarchi, R.; Antelo, M. L.; Mattos-Arruda, L. D.; Generali, D.; Caldas, C.; Munzone, E.; Dirix, L.; Delson, A. L.; Burstein, H. J.; Qadir, M.; Ma, C.; Scott, J. H.; Bidard, F. -C.; Park, J. W.; Rugo, H. S

Shifting regime shifted policy—interplay of interests in sustainability discourses of forest land use

Colonial interest, Commercial interest, Bangladesh forestry, Forest policy, Peoples participation, Policy interest, Regime change, Sustainability and tradition,