bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single domain antibody (SBT-100) crosses the blood brain barrier (BBB) and inhibits human glioblastoma by selectively targeting KRAS and P-STAT3.
Authors: Singh Sunanda , Murillo Genoveva , Singh Avani , Singh Samara , Parihar Meenakshi S , Singh Anjali H , Mehta Rajendra , Parihar Ashutosh S 
Published: September 2018

e13547 Background: Glioblastoma is difficult to treat malignancy that has a high incidence of KRAS mutations ( > 90%) and hyper-expression of P-STAT3 ( > 90%). Most chemotherapeutic agents and large biologics (four chain heterotetrameric IgG) cannot cross the BBB. Therefore Singh Biotechnology’s (SBT) propriety technology has developed a novel targeted therapy and engineered SBT-100 a 15 kD single domain antibody (sdAb) that is bispecific for KRAS and STAT3, which can cross the BBB to target gliablastomas. Methods: Human glioblastoma (U87MG) cell line was used and obtained from ATCC. Biacore affinity assay was used to demonstrate SBT-100 binding to KRAS, KRAS (G12D), and STAT3. The glioblastoma cells were incubated with 0µg/ml to 200µg/ml of SBT-100. MTT assay was performed after 3 days of treatment with SBT-100 and the growth inhibition was calculated. Xenograft (athymic nude mouse) with a well established tumor growing for 6 weeks was injected with SBT-100 intraperitoneally (IP). After 15 minutes the brain of this animal was harvested for immunohistochemical staining. Results: Biacore studies showed SBT-100 binds KRAS with affinity constant of 10-9M, KRAS (G12D) at 10-8M, and STAT3 at 10-8M. MTT assay reveals 62% (p < 0.01) growth inhibition of U87MG within 3 days. A xenograft mouse with a well established tumor ( > 150mm3), when injected IP with 5mg/kg of SBT-100 showed localization in the brain within 15 minutes. Therefore SBT-100 (sdAb) crosses the BBB, and shows intracellular localization in the animal’s neurons and glial cells. Conclusions: SBT-100 significantly inhibits the growth of glioblastoma. KRAS mutations and/or over expression of P-STAT3 in glioblastomas are promising targets for sdAbs like SBT-100, which is bispecific for KRAS and STAT3. SBT-100 crosses the BBB and localizes within the neurons and glial cells of the brain. SBT’s proprietary single domain antibody technology platform used to engineer SBT-100 holds promise for targeting primary brain malignancies, metastatic cancers that go to the brain, and for neurologic disease amenable to targeted therapy. Many chemo-resistant and radiation-resistant cancers use STAT3 as an escape mechanism.
Prognosis of leptomeningeal metastases from melanoma: A case series of 28 patients.
Authors: Oinino Sarah , Rodrigues Isabelle , Boulanger Thomas , Andre Charles , Bonneterre Jacques , Zairi Fahed , Mortier Laurent , Desmedt Eve , Templier Carole , Le Rhun Emilie 
Published: September 2018

e13550 Background: Leptomeningeal metastasis (LM) are reported in 5-25% of patients with melanoma. However, only very few large contemporary cohorts of melanoma patients with LM have been published. Methods: We report on a case series of 28 consecutive patients with LM from melanoma (BRAF mutated in 14 cases, of 19 tested) diagnosed between April 2007 and April 2016, and treated for LM using a combination of systemic treatment, intra-cerebrospinal fluid (CSF) therapy and radiotherapy according to prior treatments and the presentation of LM. Results: The median age at LM diagnosis was 49.5 years (range 27-73). Median ECOG-performance status was 2 (0-4). Concomitant brain metastases were present in all but 4 patients at LM diagnosis. LM was the first site of metastatic disease for only 2 patients. Median time from melanoma diagnosis to LM diagnosis was 0.33 years in patients with metastatic disease at melanoma diagnosis (4 patients) and 4.5 years in patients without metastatic disease at melanoma diagnosis (24 patients). First line treatment for LM was a combination of intra-CSF (liposomal cytarabine) and systemic treatments in 25 cases, and systemic treatment alone in 3 cases. Systemic treatments include chemotherapy (n = 18), targeted therapy (BRAF inhibitor n = 9; MEK inhibitor, n = 3) and immunotherapy (n = 4). No radiotherapy was performed. Ten patients received more than one line of treatment for LM. Median progression-free survival with first line treatment was 1.75 months. Responses or stabilization (for at least 2 months) were observed in only 7 patients. Median overall survival (OS) for the whole cohort was 3.08 months. Conclusions: The prognosis of patients with LM from melanoma remains poor. The role of new agents such as targeted therapies and immunotherapy for the treatment of LM is still not well defined. Adequate use of intrathecal chemotherapy, targeted therapy and immunotherapy could improve the survival of these patients.
Paradoxical behavior of time to RECIST progression as a metric for treatment effect.
Authors: Bottino Dean , Gomez Axel , Burton Jackson , Williams Katherine , White Douglas , Chakravarty Arijit 
Published: September 2018

e14022 Background: RECIST time to progression (RTTP) is the cornerstone of widely used surrogates for patient benefit such as RECIST progression-free survival (RPFS), which in turn is used either for accelerated regulatory approval or to study the effects of factors such as drug exposure and drug target expression levels on RPFS. While one might expect increased antitumor effect to result in longer RTTP and RPFS, we will show that this is often not the case due to a fundamental mathematical property of the RECIST definition of disease progression. Methods:We use a simple mathematical model that treats patient tumor burden dynamics as an evolutionary process consisting of a decreasing drug-sensitive subpopulation of tumor cells and an independently growing drug-resistant subpopulation. This model has successfully described tumor dynamics in NSCLC, melanoma (CPT Pharmacometrics Syst. Pharmacol. (2017) 6, 29–39), and ovarian cancer (internal data). In the presence of drug, we represent the net fitness of the sensitive cells in terms of an exponential decay or “kill” rate k > 0, and the net fitness of the resistant cells as an exponential growth rate g > 0, and the initial fraction of drug-resistant cells by 0 ≤ f ≤ 1. For a given virtual patient (parameter set), we simulate RTTP as the time after start of treatment at which tumor burden V(t) is 20% higher than its lowest value (per RECIST criteria). We then vary the kill rate k and check whether RTTP increases or decreases with increasing k. Results: There is a large set of parameter values for which RTTP is predicted to vary inversely with increasing kill rate k. These parameter values are attained clinically in ovarian cancer patients taking alisertib and paclitaxel (internal data). Conclusions: While RECIST progression criteria may be useful for patient care to identify when a patient is losing her response, care must be taken in interpreting RTTP as a metric of treatment effect due to the real possibility that a stronger treatment effect results in shorter RTTP. We recommend that alternative metrics for patient benefit, such as a generalization of Days Gained (Neal et al PLoS ONE 8(1)e51951), be evaluated. We will present results of these evaluations currently in progress.
Patient-reported outcomes (PRO) in cancer trials submitted to the FDA from 2012-2015.
Authors: Kanapuru Bindu , Singh Harpreet , Kim Janice , Kluetz Paul Gustav ,   U.S. Food and Drug Administration
Published: September 2018

e14024 Background: PRO measures are commonly assessed in cancer trials. We reviewed the PRO strategy, tools and trial designs for new drug applications (NDA) and biologics license applications (BLA) submitted to FDA over a 4 year period. Methods: A review of protocols and clinical study reports for original NDA and BLA applications submitted to the Office of Hematology and Oncology Products between 2012 and 2015 to support initial approval for adult malignant hematology and oncology conditions was done. We reviewed applications for inclusion of PRO data, trial design, type of PRO measure employed and statistical analysis methods. Results: Forty three trials were submitted to support 40 original NDA or BLA approvals targeting adult malignancies between 2012 and 2015. Of these 43 trials, 17/43 (40%) were accelerated approval, 26/43 (60%) were randomized, 17/43 (40%) were single arm and 27/43 (63%) were open label trials. Sponsors documented the incorporation of PRO assessments in 28/43 (65%) trials. For trials that included PRO assessments, 22/28 (79%) were randomized controlled trials, 6/28 (21%) were single arm and 17/28 (61%) were open label studies. The most common PRO instruments used were the EORTC-QLQ-C30 (15/28; 54%), EQ-5D (13/28; 46%) and various FACIT measures (8/28; 29%). Although 20/28 (71%) trials had PRO measures listed as a secondary endpoint, only 1 trial included PRO endpoints in the statistical testing hierarchy. Conclusions: PRO measures are often employed in randomized controlled cancer trials; however accelerated approval is common in oncology and trial designs are increasingly open label and single arm. Patient-focused drug development efforts will need to identify clinical trial objectives and analysis methods for PRO measures to describe symptoms and function that are suitable for these contexts. Descriptive PRO data on the tolerability of an anti-cancer agent may be one objective that is relevant across trial contexts. To support a claim of superiority, PRO endpoints should be adjusted for multiplicity by inclusion in the statistical hierarchy.
Predictive score of early mortality in patients with solid tumors enrolled in phase I clinical trials.
Authors: Ugidos Lisardo , Boni Valentina , Garralda Elena , de Miguel Luken Maria Jose , Alvarez-Gallego Rafael , Rodriguez-Pascual Jesus , Vega Estela , Munoz Cesar , Garcia-Rey Cesar , Cubillo Antonio , Calvo Emiliano 
Published: September 2018

e14029 Background: A usual inclusion criterion for phase I trials is life expectancy of more than 3 months. Prediction of early mortality (EM), in the first 90 days after starting treatment, is thus a challenge. Predictive scores may help to select more adequate patients (pts). Our main objective was to generate a predictive score in a training set of phase I pts and to confirm it in a validation score. Secondly, we figured out if our score also predicts overall survival (OS). Methods: Consecutive pts treated in our phase I unit between 2008 and 2013 were retrospectively reviewed. We collected 35 clinical and analytical characteristics at base line. Stepwise regression was used to correlate pts characteristics with EM and generate a predictive score. Log-rank regression and Kaplan Meier curves were used to study survival. Results: We identified 438 pts. Median age was 61 yr (18-87) and 52.7% were male. More frequent tumor types were gastrointestinal (37%), thoracic (17%), and breast (12%). Pts treated with chemotherapy were 32%, targeted therapy 36%, combination 29%, and immunotherapy 3%. Response rate was 12.4%. Median progression free survival (PFS) and OS were 2.6 and 8.5 months respectively. Most common causes of discontinuation were tumor progression (87.2%) and toxicity (5.7%). EM rate was 20.5%. We randomly included 243 pts in the training score. In multivariate stepwise regression, 6 features were related to EM: ECOG PS 2 (vs 0-1), gastrointestinal or thoracic tumors (vs other types), red cell counts below 4*106/ml, LDH above 600 U/L, calcium below 8.6 mg/dL, and ratio neutrophil/lymphocyte above 5. An EM score was generated ranging 0-7 (2 points for ECOG PS and 1 point for each other characteristic). Using cut off value of 0-2 vs 3 or more, we would reduce EM90 rate to half (11%) and avoid inclusion of 60% pts with EM. Our EM score was validated in the second cohort; we reduced EM rate to 10.5% avoiding undesirable inclusion of 59% pts. Applying score to all pts, median OS was 16, 8.4, 4.4, and 3 months for score 0, 1, 2, and 3-7 respectively (p < 0.01). Conclusions: Our score can avoid inclusion of 60% of pts who would die before 90 days, reducing EM rate from 20 to 10%. This score can identify four prognostic groups with different median OS.
Enrollment into molecular selection trials and impact on patient disposition.
Authors: Harvey R Donald , Steuer Conor Ernst , Judson Emma C , Lewis Colleen Margaret , Collins Hannah H , Saba Nabil F. , El-Rayes Bassel F. , Curran Walter John , Ramalingam Suresh S. , Pentz Rebecca D. , Owonikoko Taofeek Kunle 
Published: September 2018

e14035 Background: Optimal use of molecularly targeted therapies is achieved by pairing agents with driver mutations present in tumor tissue. Enrollment on clinical trials designed to demonstrate this objective requires obtaining informed consent prior to molecular analysis, with potential delays in tissue acquisition, testing results, and treatment initiation. We reviewed our experience and patient disposition with studies where assignment to treatment required mutation data. Methods: We identified trials requiring consent prior to tissue mutational analysis. Review included time intervals between landmark events starting with trial presentation to patient, consent, tissue shipment, mutation analysis results, and if and when treatment was initiated. Demographic data, change in ECOG PS, and subsequent therapy were also collected. Patients were included in the analysis if they signed consent. Results: Experience with 68 patients consented across 4 molecular selection trials was reviewed. Median age: 60 years (32-87); 56% female; self-identified race White (72%), African-American (24%), Asian (4%). Most common cancers were lung (35%), colorectal (18%), parotid (7%) and sarcoma (7%). Nineteen patients required new biopsies; 15 patients (22%) discontinued participation prior to molecular results being available. Common reasons for discontinuation included insufficient archival tissue (5), lost to follow up, initiation of other treatment, and death (2 each). In 53 patients who continued, overall median time from consent to test results received was 41 days (12-149); with median time from consent to obtaining tissue of 22 days (0-121), and tissue sent to results received was 13 days (1-77). In those with advanced disease (n = 36), PS worsening occurred in 28%. Three patients matched to therapy; 1 received more than 1 cycle. In those not matching (n = 50), 46% received approved therapies, 22% were lost to follow-up, 18% enrolled on another trial and 14% died. Conclusions: Molecular selection of patients for clinical trials requires additional time and resources, and many patients do not have driver mutations. Long time intervals between decision points can delay therapies and impair the ability to explore alternative treatment.
The incidence and risks of adverse events in randomized controlled trials (RCTs) of cancer drugs downplaying the harms.
Authors: Gyawali Bishal , Honda Kazunori , Shimokata Tomoya , Ando Yuichi 
Published: September 2018

e14036 Background: Proper assessment of harms of cancer treatment is essential to make risk-benefit trade off decisions in oncology clinic. CONSORT guidelines require the authors of RCTs to provide exact data for adverse events (AEs) grade 3 or higher (severe AEs), serious AEs (SAEs) and fatal AEs (FAEs) and avoid using general terms (such as well-tolerated) that downplay the harms. We aimed to assess the incidence and risks of severe AEs, SAEs and FAEs in such RCTs of cancer drugs that downplayed the harms. Methods: We extracted all the phase 2 and 3 RCTs of cancer drugs from the five major journals (NEJM, Lancet, Lancet Oncology, JAMA, JCO) from 2016 January to 2016 December. The abstracts/full texts of the papers were studied to assess if the harms of the experimental arm were downplayed. Use of any of the following terms while describing toxicities or AEs or safety was assumed to downplay the harms: acceptable, feasible, tolerable (or well-tolerated) , favorable, safe, manageable. Data on severe AEs, SAEs and FAEs for both the experimental and control cohorts were extracted from these RCTs and pooled using random-effects model to determine the overall incidence and risk. Results: Of 122 phase 2/3 RCTs of cancer drugs identified, 53 (43.4%) reports used terms downplaying the toxicities of the experimental arm and were included in this analysis. The overall incidence of severe AEs, SAEs and FAEs with these cancer drugs were 50.6% (95% CI: 41.5%-59.7%), 21.9% (95% CI: 16.3%-28.7%) and 1.6% (95% CI: 1.2%-2.2%) respectively. Compared with control, the risk of severe AEs and SAEs were significantly increased with the use of these cancer drugs: severe AEs (RR 1.15, 95% CI: 1.04-1.27, p = 0.005) and SAEs ( RR 1.49, 95% CI: 1.26-1.77, p < 0.001) . However, the risk of FAEs was similar across the experimental and control arms ( RR 0.89, 95% CI: 0.72-1.11, p = 0.306) Conclusions: Our analysis shows that considerable proportions of patients suffer severe AEs, SAEs and FAEs and significantly increased risk of severe AEs and SAEs in the trials that downplay the toxicities of cancer drugs. Terms that falsely downplay the toxicities of cancer drugs should be avoided in the reporting of RCTs to encourage accurate risk-benefit assessment.
Intracellular targeting of the oncogenic MUC1-C protein with a GO-203 nanoparticle formulation overcomes MCL-1- and BFL-1-mediated resistance in human carcinoma cells.
Authors: Hiraki Masayuki , Jin Caining , Alam Maroof , Maeda Takahiro , Murata Masaru , Hiratsuka Masahiro , Doki Yuichiro , Kharbanda Surender , Mori Masaki , Kufe Donald W. 
Published: September 2018

e14053 Background: Aberrant expression of MCL-1 and BFL-1, the pro-survival members of the Bcl-2 family, is a major cause of drug resistance in human cancers. Mucin 1 (MUC1) is a heterodimeric oncoprotein that is aberrantly expressed in most human carcinomas. Notably, there is no known relationship between the oncogenic MUC1 C-terminal subunit (MUC1-C) and these anti-apoptotic proteins. Methods: MUC1-C was targeted in breast, lung and colon cancer cells by a stable shRNA, a tetracycline-inducible shRNA, or a pharmacologic peptide inhibitor GO-203. MCL-1 was inhibited by siRNA or the MS-1 peptide. In vitro and in vivo studies were conducted using our polymeric nanoparticles (NPs) for intracellular delivery of peptide cargos. Cells were selected for resistance to ABT-737 or ABT-263, which target BCL-2, BCL-XL and BCL-w, but not MCL-1 and BFL-1. Results: Targeting MCL-1 with MS-1/NPs inhibited the survival of parental cancer cells in vitro and in vivo, and was associated with upregulation of BFL-1 levels. In addition, MS-1/NPs treatment had limited effects on ABT-resistant cells because of increased BFL-1 expression. Importantly, we found that targeting MUC1-C is associated with suppression of both MCL-1 and BFL-1. Mechanistically, MUC1-C (i) stabilizes MCL-1 by activating the MEK→ERK and PI3K→AKT pathways, and (ii) induces BFL-1 through the NF-κB p65 pathway. Treatment with GO-203/NPs suppressed proliferation of parental and ABT-resistant cells. In addition, we show that combining GO-203 with ABT-737 is synergistic in inhibiting survival of parental and ABT-resistant cells. Conclusions: These findings demonstrate that targeting MUC1-C with GO-203/NPs is a potential strategy for abrogating MCL-1- and BFL-1-mediated resistance.
The activity of the HDAC inhibitor HBI-8000 (Chidamide) combined with eribulin on 4T1 spontaneous metastasis development.
Authors: Bissonnette Reid Paul , Rolland Alain , Goodenow Bob , Gillings Mireille 
Published: September 2018

e14055 Background: In preclinical studies eribulin has shown significant effects on epithelial-mesenchymal transition (EMT) in human breast cancer cells in vitro and in vivo, inducing a switch from mesenchymal to epithelial states, decreasing migration and invasiveness of human breast cancer cells in vitro, as well as experimental metastases in vivo. HBI-8000 is a novel, orally bioavailable Class I selective HDAC inhibitor (HDACi). In addition to its demonstrated positive effects on antitumor immunity, it also exerts significant effects on EMT pathway components, enhancing CDH1 (e-cadherin) expression and inhibiting TGF-β induced metastasis. Methods: The syngeneic, orthotopic 4T1 model is thought to be a close representation of the clinical situation; similar to human mammary carcinoma, the major cause of morbidity and mortality is development of spontaneous metastases. 4T1-implanted mice treated with combinations of eribulin and HBI-8000 were monitored for primary tumor growth inhibition (TGI), survival, and metastatic lung foci. Tumor samples were analyzed by Q-PCR for expression of genes involved in EMT or in the metastatic process. Results: Eribulin alone had no effect on primary TGI. Eribulin combined with HBI-8000 resulted in significant (P < 0.05) reductions in median tumor volume, tumor volume distribution (TMD) and survival (P < 0.005). Single agent HBI-8000 had a similar effect on TGI, TMD (P < 0.05) and survival (P < 0.005). Whereas single agent HBI-8000 or eribulin failed to significantly reduce metastases, the eribulin-HBI-8000 combination produced significant (P < 0.01) and synergistic inhibition of metastases, decreasing the number of lung foci approximately 10-fold. Gene expression analyzed by Q-PCR revealed correlations between metastasis blockade and increases in E-Cadherin, Occludin and Claudin1. There was a strong correlation with inhibition of HMGA2 (High Mobility Group AT-Hook 2) gene expression. Conclusions: Eribulin combined with HBI-8000 inhibited primary tumor growth and inhibited metastasis development and increased survival. This effect was correlated and consistent with changes in genes relevant to EMT, tumor plasticity and stemness.
Characterization of URST1 as a prognostic biomarker and therapeutic target for lung and oral cancers.
Authors: Takano Atsushi , Yoshitake Yoshihiro , Shinohara Masanori , Miyagi Yohei , Daigo Yataro ,   Research Hospital, Institute of Medical Science, The University of Tokyo
Published: September 2018

e14057 Background:Lung cancer and oral cavity cancer belong to aerodigestive cancers whose clinical outcome after multimodal therapy remains poor. Methods:To identify new biomarkers and therapeutic targets for lung and oral cancers, we screened genes using our original gene expression profile database for various solid cancers, and characterized clinical and oncogenic values of up-regulated in solid tumor 1 (URST1) protein as a candidate. Results: URST1 was highly expressed in the most of lung or oral cancer cell lines and tumor tissues, but was hardly detected in normal lung or oral epithelial cells and tissues as detected by real-time PCR and western blot analyses. Immunocytochemical analysis revealed that URST1 was mainly localized in the nucleus and cytoplasm of lung or oral cancer cell lines. Immunohistochemical analysis using tissue microarray showed that positive staining of URST1 was observed in 231 of 358 (64.5%) lung cancers, but not in normal lung, and it was significantly associated with poor prognosis after curative surgery. In addition, URST1 was expressed in 64 of 96 (66.7%) oral cancers, but not in oral mucosa, and it was significantly correlated with poor clinical outocome after surgery. Multivariate analysis confirmed that URST1 expression was an independent prognostic factor for oral cancer. Suppression of URST1 expression by siRNA or treatment with synthesized inhibitor specific for URST1 activity inhibited mitosis and growth of lung or oral cancer cell lines. Conclusions:URST1 is likely to be a prognostic biomarker and therapeutic target for aerodigestive cancers such as lung and oral cancers.