BACKGROUND:Colorectal cancer (CRC) metastasis remains a major cause of mortality, driven by epithelial-to-mesenchymal transition (EMT) and invasion. Programmed cell death 4 (Pdcd4), a tumor suppressor, is known to inhibit translation via interaction with eukaryotic initiation factor 4A (eIF4A). Previous studies have established that Pdcd4 suppresses stress-activated protein kinase 1-interacting protein 1 (Sin1) translation through the mTORC2-Akt axis, thereby downregulating Snail expression and EMT in CRC cells. However, whether Pdcd4 directly regulates Slug, another critical EMT transcription factor, remains unexplored. METHOD:PDCD4 shRNA and SLUG siRNA were used to knock down Pdcd4 and Slug in colorectal cancer cells, respectively. The sucrose gradient fractionation was performed to determine SLUG translation. A luciferase reporter assay was used to determine the role of the SLUG 5' untranslated region (5'UTR) on Pdcd4 inhibition. The effect of Slug on promoting invasion was determined by Matrigel invasion assays. RESULT:Knockdown of Pdcd4 in colorectal cancer cells increased Slug protein levels without altering SLUG mRNA abundance. Sucrose gradient fractionation revealed that Pdcd4 knockdown elevated the proportion of SLUG mRNA in polysome fractions, demonstrating Pdcd4-mediated suppression of SLUG translation. To validate the mechanism, the SLUG 5'UTR was cloned and fused to a luciferase reporter and named SLUG-5'UTR-Luc. Pdcd4 knockdown markedly enhanced SLUG-5'UTR-Luc activity; whereas, ectopic Pdcd4 expression suppressed it, indicating that the SLUG 5'UTR is critical for Pdcd4-mediated translational repression. Treatment with the eIF4A inhibitor silvestrol substantially reduced Slug protein levels and SLUG-5'UTR-Luc activity. In addition, Pdcd4 overexpression decreased Slug protein abundance and restored E-cadherin expression. Notably, Slug knockdown in Pdcd4-deficient cells rescued E-cadherin expression and abrogated the invasive phenotype. These findings suggest that up-regulation of Slug translation by Pdcd4 knockdown contributes to enhanced invasion. CONCLUSION:Pdcd4 suppresses colorectal cancer invasion by translationally downregulating Slug expression.

Purpose: Appalachian regions like Eastern Kentucky have high breast cancer mortality rates despite lower incidence rates compared to the rest of Kentucky. This area also experiences increased obesity rates. Previous studies have linked high breast density to a higher risk of breast cancer and obesity to poorer survival outcomes in other populations, but the relationship between BMI, breast density, and cancer progression in Appalachian Kentucky remains unclear. This retrospective study investigates these links in breast cancer patients from the region. Methods: We analyzed mammogram images of 1,405 women diagnosed with breast cancer at Markey Cancer Center between 2000-2018. Data on BMI, mammogram density, and cancer progression were collected. Mammograms were scored using the BI- RADS breast density scale. Additional data included age at diagnosis, BMI within a year of diagnosis, cancer stage, and treatment follow-up. Kaplan-Meier curves, log-rank tests, and Spearman correlation assessed the relationships among survival, BMI, and breast density. Results: A significant negative correlation between BMI and breast density was found (Spearman correlation=-0.34; P < 0.0001). However, no significant associations were observed between breast density, obesity, and overall survival. The worst survival was seen in patients with BMI <= 18.5. Conclusion: In Appalachian Kentucky, BMI negatively correlates with breast density, but neither breast density nor obesity significantly impacts breast cancer prognosis. Underweight patients had poorer survival outcomes, suggesting factors other than obesity and breast density influence prognosis in this demographic.

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method’s ability to recover the temporal order of pathway mutations in several cancer types.

Supplementary Figure S6: Over-expression of Pdcd4 inhibits OSI-906 induced phospho-P70S6K1

Supplementary Figure S8: Knockdown of Pdcd4 enhances OSI-906 induced phospho-P70S6K1

Supplementary Figure S2: Over-expression of Pdcd4 enhances the anti-proliferation effects of OSI-906

Supplementary Figure S1: The expression level of Pdcd4 correlates with cell sensitivity to OSI-906

With the rapid development of new anti‐cancer agents which are cytostatic, new endpoints are needed to better measure treatment efficacy in phase II trials. For this purpose, Von Hoff (1998) proposed the growth modulation index (GMI), that is, the ratio between times to progression or progression‐free survival times in two successive treatment lines. An essential task in studies using GMI as an endpoint is to estimate the distribution of GMI. Traditional methods for survival data have been used for estimating the GMI distribution because censoring is common for GMI data. However, we point out that the independent censoring assumption required by traditional survival methods is always violated for GMI, which may lead to severely biased results. In this paper, we construct both nonparametric and parametric estimators for the distribution of GMI, accounting for the dependent censoring of GMI. Extensive simulation studies show that our nonparametric estimators perform well in practical situations and outperform existing estimators, and our parametric estimators perform better than our nonparametric estimators and existing estimators when the parametric model is correctly specified. A phase II clinical trial using GMI as the primary endpoint is provided for illustration.

T-cell-based immunotherapy revolutionized the treatment of immune suppressive cancers. Blocking T cell inhibitory receptors such as programmed death 1 (PD1) or their ligands (like PD-L1) enhances antitumor T cell responses. However, many cancers employ multiple methods of immune suppression, including the production of potent regulatory cytokines like Interleukin-10 (IL-10). B cell Chronic Lymphocytic Leukemia (CLL) is one such B cell malignancy that elicits widespread immune dysfunction including numerous functional deficits in T cells. Human and mouse CLL cells (Eμ-Tcl1) produce IL-10 and PD-L1, which dampen antitumor immunity. Since immune checkpoint blockade experienced limited success in CLL, we investigated IL-10 suppression as a novel combination therapy. Exogenous and CLL-derived IL-10 decreased human and mouse T cell functionality in vitro. Further, CLL-derived IL-10 can be blocked with antibodies or can be reduced with small molecule inhibitors to improve CD8+ T cell functionality in vivo. CLL IL-10 production depends on the transcription factor Sp1. Hence, we utilized a novel analogue of the Sp1 inhibitor mithramycin to reduce CLL IL-10 secretion. IL-10 inhibition improved responses to anti-PD-L1 therapy, with increased survival and decreased CLL burden compared to anti-PD-L1 alone. This method improved CD8+ T cell proliferation, effector-memory cell frequency, and interferon-γ production. CD8+ T cells were also more abundant, with fewer exhausted T cells even at very advanced stages of disease. Current cancer therapies do not target IL-10 and our studies provide evidence for targeting IL-10 to increase the efficacy of T cell immunotherapies in human CLL, and possibly other cancers with T cell suppression.

T-cell dysfunction is a hallmark of B-cell Chronic Lymphocytic Leukemia (CLL), where CLL cells downregulate T-cell responses through regulatory molecules including programmed death ligand-1 (PD-L1) and Interleukin-10 (IL-10). Immune checkpoint blockade (ICB) aims to restore T-cell function by preventing the ligation of inhibitory receptors like PD-1. However, most CLL patients do not respond well to this therapy. Thus, we investigated whether IL-10 suppression could enhance antitumor T-cell activity and responses to ICB. Since CLL IL-10 expression depends on Sp1, we utilized a novel, better tolerated analogue of the Sp1 inhibitor mithramycin (MTMox32E) to suppress CLL IL-10. MTMox32E treatment inhibited mouse and human CLL IL-10 production and maintained T-cell effector function in vitro. In the Eμ-Tcl1 mouse model, treatment reduced plasma IL-10 and CLL burden and increased CD8+ T-cell proliferation, effector and memory cell prevalence, and interferon-γ production. When combined with ICB, suppression of IL-10 improved responses to anti-PD-L1 as shown by a 4.5-fold decrease in CLL cell burden compared to anti-PD-L1 alone. Combination therapy also produced more interferon-γ+, cytotoxic effector KLRG1+, and memory CD8+ T-cells, and fewer exhausted T-cells. Since current therapies for CLL do not target IL-10, this provides a novel strategy to improve immunotherapies.

The insulin-like growth factor 1 receptor (IGF-1R) governs several signaling pathways for cell proliferation, survival, and anti-apoptosis. Thus, targeting IGF-1R appears as a reasonable rationale for tumor treatment. However, clinical studies showed that inhibition of IGF-1R has very limited efficacy due to the development of resistance to IGF-1R blockade in tumor cells. Here, we discovered that prolonged treatment of colon cancer cells with IGF-1R inhibitors (BMS-754807 and GSK1838705A) stimulates p70 KDa ribosomal protein S6 kinase 1 (p70S6K1) activation, a well-known kinase signaling for cell survival. We also found that p70S6K1 activation by IGF-1R inhibition is independent of K-Ras and PIK3CA mutations that frequently occur in colon cancer. Besides the increased p70S6K1 phosphorylation, the phosphorylation of mitogen-activated protein kinase kinase 1 and 2 (MEK1/2) was elevated in the cells treated with BMS-754807. Interestingly, the increases in MEK1/2 and p70S6K1 phosphorylation were also observed when cells were subjected to the treatment of AKT inhibitor or genetic knockdown of AKT2 but not AKT1, suggesting that AKT2 inhibition stimulates MEK1/2 phosphorylation to activate p70S6K1. Conversely, inhibition of MEK1/2 by MEK1/2 inhibitor (U0126) or knockdown of MEK1 and MEK2 by corresponding mek1 and mek2 siRNA enhanced AKT phosphorylation, indicating mutual inhibition between AKT and MEK. Furthermore, the combination of BMS-754807 and U0126 efficiently decreased the cell viability and increased cleaved caspase 3 and apoptosis in vitro and in vivo. Our data suggest that the treatment of colon tumor cells with IGF-1R inhibitors stimulates p70S6K1 activity via MEK1/2 to promote survival, providing a new strategy for colorectal cancer therapeutics.

Additional file 2 Table S1 provides a list of “core” pathway genes in each of the 9 key cancer pathways considered in the paper.

Recently, molecularly targeted agents and immunotherapy have been advanced for the treatment of relapse or refractory cancer patients, where disease progression‐free survival or event‐free survival is often a primary endpoint for the trial design. However, methods to evaluate two‐stage single‐arm phase II trials with a time‐to‐event endpoint are currently processed under an exponential distribution, which limits application of real trial designs. In this paper, we developed an optimal two‐stage design, which is applied to the four commonly used parametric survival distributions. The proposed method has advantages compared with existing methods in that the choice of underlying survival model is more flexible and the power of the study is more adequately addressed. Therefore, the proposed two‐stage design can be routinely used for single‐arm phase II trial designs with a time‐to‐event endpoint as a complement to the commonly used Simon's two‐stage design for the binary outcome.

Molecularly targeted, genomic-driven, and immunotherapy-based clinical trials continue to be advanced for the treatment of relapse or refractory cancer patients, where the growth modulation index (GMI) is often considered a primary endpoint of treatment efficacy. However, there little literature is available that considers the trial design with GMI as the primary endpoint. In this article, we derived a sample size formula for the score test under a log-linear model of the GMI. Study designs using the derived sample size formula are illustrated under a bivariate exponential model, the Weibull frailty model, and the generalized treatment effect size. The proposed designs provide sound statistical methods for a single-arm phase II trial with GMI as the primary endpoint.

In environmental exposure studies, it is common to observe a portion of exposure measurements to fall below experimentally determined detection limits (DLs). The reverse Kaplan–Meier estimator, which mimics the well‐known Kaplan–Meier estimator for right‐censored survival data with the scale reversed, has been recommended for estimating the exposure distribution for the data subject to DLs because it does not require any distributional assumption. However, the reverse Kaplan–Meier estimator requires the independence assumption between the exposure level and DL and can lead to biased results when this assumption is violated. We propose a kernel‐smoothed nonparametric estimator for the exposure distribution without imposing any independence assumption between the exposure level and DL. We show that the proposed estimator is consistent and asymptotically normal. Simulation studies demonstrate that the proposed estimator performs well in practical situations. A colon cancer study is provided for illustration. Copyright © 2017 John Wiley & Sons, Ltd.

BACKGROUND:Most metastatic spinal cord lesions are located either in the intradural, extramedullary, or in the epidural compartments. Intramedullary spinal cord metastasis (ISCM) is a rare central nervous system spread of cancer. The aim of this report was to evaluate ISCM in the published literature. METHODS:A literature review of PubMed from 1960 to 2016 was undertaken for the publications having demographic, clinical, histological, and outcome data. RESULTS:A total of 59 relevant papers were identified, showing 128 cases of intramedullary metastasis from lung cancer. The incidence of lung cancer as the primary malignancy with intramedullary metastasis was 56%. The median time from diagnosis of primary to intramedullary metastasis was 6months. Survival improved with multimodality therapy compared to monotherapy (4monthsvs. 6.3months) (hazard ratio=0.501; 95% confidence interval, 0.293-0.857). CONCLUSION:Lung cancer is the predominant cause of intramedullary involvement of the spinal cord. Overall prognosis is poor, although a multimodality approach was associated with improved survival.

We report on hematologic toxicities encountered during a clinical trial using everolimus for metastatic breast cancer. Anemia, thrombocytopenia, and leukopenia were common but mild. Microcytosis and reduced red cell hemoglobin content were consistently observed during treatment. Although total white blood cell counts remained stable, there was a progressive decrease of lymphocyte percentage over time with a trend for increased neutrophils.Background: Everolimus, which inhibits the mammalian target of rapamycin (mTOR), is increasingly used in breast cancer and familiarity with its full range of toxicity is critical for practicing oncologists. Patients and Methods: We studied hematologic changes in 31 patients with metastatic breast cancer treated in a phase II clinical trial using everolimus. Complete blood counts were collected at baseline, 2 weeks, 4 weeks, every 4 weeks during treatment, and 1 month after discontinuation. Adverse events were defined using Common Toxicity Criteria version 3. Linear mixed models with fixed effects of time and random intercepts and slopes were used to study trends and comparisons were conducted using paired t tests. Results: Anemia was reported in 22 patients (71%), thrombocytopenia in 17 (55%), and leukopenia in 14(45%). These were predominantly grade 1 or 2 and did not require dose modification. Red blood cell mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) both decreased significantly over time p < .0001) starting at 2 weeks with no significant change in mean corpuscular hemoglobin concentration (MCHC) P = .104). Both MCV and MCH increased 1 month after treatment discontinuation (P values < .0001 and < .0003, respectively) indicating reversibility of this effect. Although total leukocyte counts remained largely stable, lymphocyte percentage progressively decreased over time with a trend for increased neutrophils. Conclusion: In addition to anemia, leukopenia, and thrombocytopenia, everolimus consistently induces red cell microcytosis and reduced hemoglobin content. Lymphopenia may contribute to immune suppression and increased risk of infection. Familiarity with these hematologic changes is prudent as more patients are treated with this class of drugs.

Abstract Agents targeting insulin-like growth factor 1 receptor (IGF-1R) are being actively examined in clinical trials. Although there has been some initial success of single-agent targeting IGF-1R, attempts in later studies failed because of resistance. This study aimed to understand the effects of programmed cell death 4 (Pdcd4) on the chemosensitivity of the IGF-1R inhibitor OSI-906 in colorectal cancer cells and the mechanism underlying this impact. Using OSI-906–resistant and –sensitive colorectal cancer cells, we found that the Pdcd4 level directly correlates with cell chemosensitivity to OSI-906. In addition, tumors derived from Pdcd4 knockdown cells resist the growth inhibitory effect of OSI-906 in a colorectal cancer xenograft mouse model. Moreover, Pdcd4 enhances the antiproliferative effect of OSI-906 in resistant cells through suppression of p70S6K1 activation. Knockdown of p70S6K1, but not p70S6K2, significantly increases the chemosensitivity of OSI-906 in cultured colorectal cancer cells. Furthermore, the combination of OSI-906 and PF-4708671, a p70S6K1 inhibitor, efficiently suppresses the growth of OSI-906–resistant colon tumor cells in vitro and in vivo. Taken together, activation of p70S6K1 that is inhibited by Pdcd4 is essential for resistance to the IGF-1R inhibitor in colon tumor cells, and the combinational treatment of OSI-906 and PF-4708671 results in enhanced antiproliferation effects in colorectal cancer cells in vitro and in vivo, providing a novel venue to overcome the resistance to the IGF-1R inhibitor in treating colorectal cancer. Mol Cancer Ther; 14(3); 799–809. ©2015 AACR.

Background: MicroRNAs (miRNAs) may serve as biomarkers for breast cancer (BC) diagnosis and prognosis. Since their clinical value based on race/ethnicity and molecular subtypes has not been studied, we evaluated the prognostic significance of a panel of miRNAs in luminal and triple-negative BCs (TNBCs) of African Americans (AAs) and non-Hispanic Caucasians (CAs). Methods: TaqMan® assays were used to quantify levels of miR-21, miR-106a, miR-206, miR-155, miR-210, and miR-335 in 151 BCs and corresponding normal tissues of 80 AAs (luminal = 24 and TNBCs = 56) and 71 CAs (luminal = 27 and TNBC = 44). Fold changes in levels between tumor-normal pairs were used to categorize the tumors into high- and low-expression groups. The levels of miRNAs were correlated with molecular subtype, patient race/ethnicity, and overall survival by Kaplan-Meier univariate and Cox regression multivariate analyses. Further, the added predictive value of these miRNAs to a baseline prediction model consisting of standard clinical risk factors was evaluated at 2-, 5-, and 8-years post-surgery based on positive predictive curves. Results: In BC tissues, miR-21, miR-106a, miR-155, miR-206, and miR-210 were up-regulated, and miR-335 was down-regulated. For the combined population, univariate and multivariate analyses showed that high levels of miR-21 (adjusted HR = 2.91, 95% CI: 1.27-6.62) and miR-106a (adjusted HR = 2.49, 95% CI: 1.04-5.97) and down-regulation of miR-335 (adjusted HR = 2.97, 95% CI: 1.35-5.54) were associated with poor survival. In multivariate analyses by race, high miR-21 (HR = 7.35, 95% CI: 2.46-21.98) and low miR-335 (HR = 14.13, 95% CI: 2.93-68.13) were indicators of poor survival in only CA patients. Additionally, expression levels of miR-21 aided in identifying risk of death in CA patients with either molecular subtype. In CAs, differences in the area under the positive predictive curve (ΔAUC) between the models with and without miR-21 were 0.077 (95% CI = 0.007-0.154) and 0.053 (95% CI = 0.002-0.128) at 5 and 8 years after surgery, respectively. In TNBCs of both racial groups, addition of miR-106a increased predictive accuracy at 5 (ΔAUC = 0.026, 95% CI = 0.001-0.068) and 8 years (ΔAUC = 0.022, 95% CI = 0-0.061) post-surgery. No miRNA was helpful in identifying patients at high risk of death due to luminal BCs or to AA ethnicity. Conclusions: High levels of miR-106a and miR-21 and low levels of miR-335 are independent prognostic markers of BCs. Furthermore, miR-21 has added predictive value above the standard clinical risk factors for CAs and miR-106a has added predictive value for TNBCs. In evaluation of the clinical utility of miRNAs, patient race and molecular types of BCs should be considered. This work was supported by a pilot grant from UAB Breast SPORE grant of the National Institutes of Health/National Cancer Institute (5P50CA089019). Citation Format: Balananda-Dhurjati Kumar Putcha, Trafina Jadhav, Michael P. Behring, Sejong Bae, Andra R. Frost, Isam-Eldin Eltoum, Li Chen, Heidi L. Weiss, William E. Grizzle, Upender Manne. Prognostic value of miRNAs in breast cancer varies with patient race and molecular subtype. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4004. doi:10.1158/1538-7445.AM2015-4004