Mitosis-specific agents have, to date, not been clinically successful. By contrast, microtubule-targeting agents (MTAs) have a long record of success, usually attributed to the induction of mitotic arrest. Indeed, it was this success that led to the search for mitosis-specific inhibitors. We believe the clinical disappointment of mitosis-specific inhibitors stands as evidence that MTAs have been successful not only by interfering with mitosis but, more importantly, by disrupting essential interphase cellular mechanisms. In this Perspective we will review literature that supports a paradigm shift in how we think about one of our most widely used classes of chemotherapeutics-MTAs. We believe that the steady presence and constant physiological role of microtubules are responsible for the overall success of MTAs. While mitosis-specific inhibitors are effective on only a small fraction of the tumor mass (dividing cells), MTAs target tubulin, a protein that has crucial roles in both mitotic and non-mitotic cells.

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The paradigm that microtubule-targeting agents (MTAs) cause cell death via mitotic arrest applies to rapidly dividing cells but cannot explain MTA activity in slowly growing human cancers. Many preferred cancer regimens combine a MTA with a DNA-damaging agent (DDA). We hypothesized that MTAs synergize with DDAs by interfering with trafficking of DNA repair proteins on interphase microtubules. We investigated nine proteins involved in DNA repair: ATM, ATR, DNA-PK, Rad50, Mre11, p95/NBS1, p53, 53BP1, and p63. The proteins were sequestered in the cytoplasm by vincristine and paclitaxel but not by an aurora kinase inhibitor, colocalized with tubulin by confocal microscopy and coimmunoprecipitated with the microtubule motor dynein. Furthermore, adding MTAs to radiation, doxorubicin, or etoposide led to more sustained γ-H2AX levels. We conclude DNA damage-repair proteins traffic on microtubules and addition of MTAs sequesters them in the cytoplasm, explaining why MTA/DDA combinations are common anticancer regimens.

Background. Tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR) have been evaluated in patients with metastatic and advanced non-small cell lung cancer (NSCLC).The U.S. Food and Drug Administration initially granted accelerated approval to gefitinib but subsequently rescinded the authorization. Erlotinib and afatinib are similar compounds approved for the treatment of metastatic NSCLC. The objective of this study was to compare the efficacy and toxicity of erlotinib, gefitinib, and afatinib in NSCLC. Methods. We tabulated efficacy variables including overall response rate (ORR), progression-free survival (PFS), and overall survival (OS) and quantitated toxicities and rates of dose reductions and discontinuation. Summary odds ratios were calculated using random and fixed-effects models. An odds ratio was the summary measure used for pooling of studies. Results. We examined 28 studies including three randomized trials with afatinib. Clinical toxicities, including pruritus, rash,

Key Points MAPK pathway activation and Bim loss may represent a fundamental mechanism of resistance to histone deacetylase inhibitors. Combination of romidepsin with an MEK inhibitor may lead to greater responses in cancers in which the MAPK pathway is active.

Purpose We applied a method that analyzes tumor response, quantifying the rates of tumor growth (g) and regression (d), using tumor measurements obtained while patients receive therapy. We used data from the phase III trial comparing sunitinib and interferon-alfa (IFN-α) in metastatic renal cell carcinoma (mRCC) patients. Methods The analysis used an equation that extracts d and g. Results For sunitinib, overall survival (OS) was strongly correlated with log g (Rsq=0.44, p<0.0001); much less with log d (Rsq=0.04; p=0.0002). The median g of tumors in these patients (0.00082 per days; log g=−3.09) was about half that (p<0.001) of tumors in patients receiving IFN-α (0.0015 per day; log g=−2.81). With IFN-α, the OS/log g correlation (Rsq=0.14) was weaker. Values of g from measurements obtained by study investigators or central review were highly correlated (Rsq=0.80). No advantage resulted in including data from central review in regressions. Further, g can be estimated accurately four months before treatment discontinuation. Extrapolating g in a model that incorporates survival generates the hypothesis that g increased after discontinuation of sunitinib but did not accelerate. Conclusions In patients with mRCC, sunitinib reduced tumor growth rate, g, more than did IFN-α. Correlating g with OS confirms earlier analyses suggesting g may be an important clinical trial endpoint, to be explored prospectively and in individual patients.

Purpose: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of tumors to nivolumab, docetaxel, and gefitinib.Experimental Design: Data were collected prospectively and analyzed retrospectively across multicenter clinical trials [nivolumab, n ¼ 92, CheckMate017 (NCT01642004), Check-Mate063 (NCT01721759); docetaxel, n ¼ 50, CheckMate017; gefitinib, n ¼ 46, (NCT00588445)]. Patients were randomized to training or validation cohorts using either a 4:1 ratio (nivolumab: 72T:20V) or a 2:1 ratio (docetaxel: 32T:18V; gefitinib: 31T:15V) to ensure an adequate sample size in the validation set. Radiomics signatures were derived from quantitative analysis of early tumor changes from baseline to first on-treatment assessment. For each patient, 1,160 radiomics features were extracted from the largest measurable lung lesion. Tumors were classified as treatment sensitive or insensitive; reference standard was median progression-free survival (NCT01642004, NCT01721759) or surgery (NCT00588445). Machine learning was implemented to select up to four features to develop a radiomics signature in the training datasets and applied to each patient in the validation datasets to classify treatment sensitivity.Results: The radiomics signatures predicted treatment sensitivity in the validation dataset of each study group with AUC (95 confidence interval): nivolumab, 0.77 (0.55-1.00); docetaxel, 0.67 (0.37-0.96); and gefitinib, 0.82 (0.53-0.97). Using serial radiographic measurements, the magnitude of exponential increase in signature features deciphering tumor volume, invasion of tumor boundaries, or tumor spatial heterogeneity was associated with shorter overall survival.Conclusions: Radiomics signatures predicted tumor sensitivity to treatment in patients with NSCLC, offering an approach that could enhance clinical decision-making to continue systemic therapies and forecast overall survival.

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