Though used widely in cancer therapy, paclitaxel only elicits a response in a fraction of patients. A strong determinant of paclitaxel tumor response is the state of microtubule dynamic instability. ...However, whether the manipulation of this physiological process can be controlled to enhance paclitaxel response has not been tested. Here, we show a previously unrecognized role of the microtubule-associated protein CRMP2 in inducing microtubule bundling through its carboxy terminus. This activity is significantly decreased when the FER tyrosine kinase phosphorylates CRMP2 at Y479 and Y499. The crystal structures of wild-type CRMP2 and CRMP2-Y479E reveal how mimicking phosphorylation prevents tetramerization of CRMP2. Depletion of FER or reducing its catalytic activity using sub-therapeutic doses of inhibitors increases paclitaxel-induced microtubule stability and cytotoxicity in ovarian cancer cells and in vivo. This work provides a rationale for inhibiting FER-mediated CRMP2 phosphorylation to enhance paclitaxel on-target activity for cancer therapy.
In this paper we propose a symbolic method for solving quasi-birth-and-death processes via the RG factorization, and some “simple truncations”—see Remark 4. For reasons yet unexplained, this symbolic ...method yields the exact G, U, and R matrices in some low dimensional cases like the
M
/
M
/
c
/
c
retrial queue with
c
=1,2 servers (these results are essentially known due to Liu and Zhao (
2010
)), as well as the “Lie solvable model” introduced by Kawanishi (
2005
) (again only for
c
=1,2).
Current screening methods for ovarian cancer can only detect advanced disease. Earlier detection has proved difficult because the molecular precursors involved in the natural history of the disease ...are unknown. To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points over three years from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). The functional and clinical significance of the identified mutations was examined using a combination of population-based whole genome sequencing, targeted deep sequencing, multi-center analysis of protein expression, loss of function experiments in an in-vivo reporter assay and mammalian models, and gain of function experiments in primary cultured fallopian tube epithelial (FTE) cells. We identified frequent mutations involving a 40kb distal repressor region for the key stem cell differentiation gene SOX2. In the apparently normal FTE, the region was also mutated. This was associated with a profound increase in SOX2 expression (p<2−16), which was not found in patients without cancer (n=108). Importantly, we show that SOX2 overexpression in FTE is nearly ubiquitous in patients with HGSOCs (n=100), and common in BRCA1-BRCA2 mutation carriers (n=71) who underwent prophylactic salpingo-oophorectomy. We propose that the finding of SOX2 overexpression in FTE could be exploited to develop biomarkers for detecting disease at a premalignant stage, which would reduce mortality from this devastating disease.
•Dense sequencing of an ovarian cancer identifies founder non-coding mutations.•Fallopian tube SOX2 overexpression is a common premalignant feature in ovarian cancer.•The expression of SOX2 and MYC in the fallopian tube appears mutually exclusive.
A major obstacle for effective early detection of ovarian cancer is that CA125 and ultrasound can only detect established ovarian cancer. Currently proposed pre-cancer lesions are not amenable to clinical detection because they affect only a small number of cells. In this work we demonstrated that pre-cancer SOX2 overexpression in the FTE is nearly ubiquitous in HGSOCs and is also a common feature in women with BRCA1 and BRCA2 mutations prior to ovarian cancer initiation. Thus, our data has important implications for screening, although it will need additional clinical evaluation to test the feasibility of quantitative detection of SOX2 expression or the expression of its downstream targets for this purpose.
The adipocyte-rich microenvironment forms a niche for ovarian cancer metastasis, but the mechanisms driving this process are incompletely understood. Here we show that salt-inducible kinase 2 (SIK2) ...is overexpressed in adipocyte-rich metastatic deposits compared with ovarian primary lesions. Overexpression of SIK2 in ovarian cancer cells promotes abdominal metastasis while SIK2 depletion prevents metastasis in vivo. Importantly, adipocytes induce calcium-dependent activation and autophosphorylation of SIK2. Activated SIK2 plays a dual role in augmenting AMPK-induced phosphorylation of acetyl-CoA carboxylase and in activating the PI3K/AKT pathway through p85α-S154 phosphorylation. These findings identify SIK2 at the apex of the adipocyte-induced signaling cascades in cancer cells and make a compelling case for targeting SIK2 for therapy in ovarian cancer.
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•SIK2 is highly expressed in adipocyte-rich metastases•SIK2 is required for adipocyte-induced proliferation of ovarian cancer metastasis•SIK2 promotes ovarian cancer cell fatty acid oxidation through ACC phosphorylation•SIK2 activates the PI3K pathway through phosphorylation of p85α at S154 and S541
Miranda et al. show that in serous ovarian cancer SIK2 is overexpressed in adipocyte-rich metastatic deposits compared with primary lesions. Adipocytes induce calcium-dependent activation and autophosphorylation of SIK2, which drives tumor cell survival and metabolism. SIK2 depletion prevents metastasis in vivo.
RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a ...mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this; within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification.
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