Showing papers by "Rodrigo Dienstmann published in 2014"

Colorectal Cancer Subtyping Consortium (CRCSC) identification of a consensus of molecular subtypes.

Abstract: 3511 Background: Recently, a number of independent groups reported novel molecular subtypes in colorectal cancer (CRC). A formal comparison across these classifiers is needed to reconcile findings ...

The evolution of our molecular understanding of colorectal cancer: what we are doing now, what the future holds, and how tumor profiling is just the beginning.

Abstract: Colorectal cancer (CRC) has been extensively molecularly characterized in recent years. In addition to the understanding of biologic hallmarks of the disease, the ultimate goal of these studies was to provide tools that could allow us to differentiate subgroups of CRC with prognostic and predictive implications. So far, subtype classification has been largely driven by well-described features: (1) defective mismatch repair resulting in higher mutation rate; (2) cellular proliferation along with chromosomal instability and copy number aberrations; and (3) an invasive stromal phenotype mainly driven by TGF-β linked to epithelial-mesenchymal transition. Recent studies have outlined the complexity of CRC at the gene expression level, confirming how heterogeneous the disease is beyond currently validated parameters, namely KRAS, BRAF mutations and microsatellite instability. In fact, adopting an extended mutation profile upfront, which includes nonrecurrent KRAS, NRAS, and PIK3CA gene variants, likely improves outcomes. In this article, we review the current trends of translational research in CRC, summarize ongoing genomically driven clinical trials, and describe the challenges for defining a comprehensive, robust, and reproducible disease classification system that links molecular features to personalized medicine. We believe that identification of CRC subtypes based on integrative genomic analyses will provide a better guide for patient stratification and for rational design of drugs targeting specific pathways.

Abstract CT325: First in human study of JNJ-42756493, a potent pan fibroblast growth factor receptor (FGFR) inhibitor in patients with advanced solid tumors

Abstract: Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: JNJ-42756493 is an FGFR 1, 2, 3, and 4 inhibitor with nanomolar affinity, orally bioavailable, and has demonstrated a broad spectrum antitumor activity in cell line, xenograft and patient-derived explant models with abnormality in FGFR signaling pathway such as FGFR gene amplification, mutation and translocation. Methods: A multipart phase 1 first in human study of JNJ-42756493 was initiated in advanced solid tumor patients ([NCT01962532][1]) including, Part 1 dose-escalation to determine the recommended phase 2 dose (RP2D) based on safety, pharmacokinetic, and pharmacodynamic data; Part 2 biopsy cohort to confirm the RP2D and Part 3 expansion phase to evaluate anti-tumor activity in NSCLC, SCLC, Breast cancer and other solid tumor patients with FGFR gene amplification, mutation or translocation at RP2D. Multiple biomarkers from tissue (including phospho-FGFR, phospho-Erk and phospho-S6) and serum (phosphate, calcium, Vitamin D, PTH and FGF23) were also assessed in the study. Results: At data cut-off (22 October 2013), total of 28 patients had been treated at 5 dose levels (0.5, 2, 4, 6 and 9 mg daily continuously) in Part 1 of the study. JNJ-42756493 appeared safe, did not generate any dose-limiting toxicities or any drug related severe adverse events. One patient from 4 mg cohort died after receiving 6 doses in Cycle 1, autopsy indicated a serious adverse event (SAE) of pulmonary edema which not related to the study drug. The most common adverse events (AEs) were hyperphosphatemia (57%), asthenia (46%), dry mouth (32%), abdominal pain (29%), diarrhea (25%), vomiting (25%), decreased appetite (21%) and constipation (21%). Grade 1 or 2 hyperphosphatemia was managed by co-administration of phosphate lowering therapy and by treatment interruption, other AEs were generally mild to moderate. No clinically significant cardiac safety findings were observed. Pharmacokinetics was linear and predictable with a half-life of ∼50 hours. Dose levels ≥ 6mg achieved plasma concentrations predicted to be efficacious from preclinical experiments. Dose dependent changes in biomarkers including increases in phosphate, FGF23 and calcium and decreases in PTH were observed in blood, evaluation of biomarker response in tissue is ongoing. A bladder cancer patient with lung metastasis harboring a FGFR3-TACC3 translocation treated at 9 mg had a confirmed PR. 9 mg was declared as the first RP2D, but safety evaluation of JNJ-42756493 at higher doses is ongoing. Conclusions: JNJ-42756493 has excellent pharmaceutical properties and appeared safe with manageable side effects at dose levels that elicit anti-tumor activity. Citation Format: Rodrigo Dienstmann, Rastilav Bahleda, Barbara Adamo, Jordi Rodon, Andrea Varga, Anas Gazzah, Suso Platero, Hans Smit, Timothy Perera, Bob Zhong, Kim Stuyckens, Yusri Elsayed, Chris Takimoto, Vijay Peddareddigari, Josep Tabernero, Feng Roger Luo, Jean-Charles Soria. First in human study of JNJ-42756493, a potent pan fibroblast growth factor receptor (FGFR) inhibitor in patients with advanced solid tumors. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr CT325. doi:10.1158/1538-7445.AM2014-CT325 [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01962532&atom=%2Fcanres%2F74%2F19_Supplement%2FCT325.atom

Stepwise group sparse regression (SGSR): Gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors

Abstract: Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines – in conjunction with modern statistical learning approaches - have been used to explore the genetic underpinnings of drug response While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, ie they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model While a purely data-driven approach offers an unbiased perspective of the data – and may yield unexpected or novel insights - this strategy introduces challenges for both model interpretability and accuracy In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss – and often an improvement - in predictive performance We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods

Prognosis and Therapeutic Implications for Emerging Colorectal Cancer Subtypes

Abstract: Although colorectal cancer was one of the first solid tumors to be characterized at the molecular level, a consensus biological classification for researchers and clinicians is lacking. Prognosis and therapy are mainly defined on the basis of patient characteristics and histopathological findings, despite studies showing that, according to mutation and gene-expression profiles, the evolution of colorectal cancer differs substantially, probably because of the high heterogeneity of the disease. In this paper we review the original molecular classifications of colorectal cancer, microsatellite and chromosomal unstable tumors, and more recent attempts to characterize the disease by using intrinsic gene expression clustering methods. These have identified at least three subtypes with different hypermutation, proliferation, and epithelial and mesenchymal features. Furthermore, we discuss preliminary data from evaluation of the potential effect of colorectal cancer subtype on prognosis and treatment response.

Unsupervised analyses reveal molecular subtypes associated to prognosis and response to therapy in colorectal cancer

Abstract: SUMMARY Colorectal cancer (CRC) tumors are highly heterogeneous at a molecular level. Recent studies have proposed molecular classifications of intrinsic CRC molecular subtypes identified after applying unsupervised clustering methods to genome-wide data. Those subtypes, characterized by their distinct clinical and biological features, provide new insight about the complexity of CRC. A common finding shared by almost all analyses was the identification of microsatellite instable tumors as an independent cluster, which is associated to better prognosis. Clusters of tumors characterized by a high stromal component exhibited a poor outcome. Moreover, some of the clusters were associated with response to standard chemotherapy or targeted agents. Regarding biological functions underlying tumor subtypes, recurrent ones across different studies were WNT pathway activation, epithelial-to-mesenchymal transition or cancer stem cell-like phenotype. Now, the challenge is to translate these findings into a comprehensi...

TGR Analysis in Phase I Clinical Trials—Letter

Abstract: There is considerable current interest in defining more precise measurements of experimental drug efficacy. Ferte and colleagues from Institute Gustave Roussy must be acknowledged for the innovative work on tumor growth rate (TGR) reduction as an early indicator of antitumor efficacy in phase I

In Focus social interactomes for enabling Research Communities

Abstract: interactome Social interactome Presentation of survey results at the conference and small group discussion Research. on November 28, 2014. © 2014 American Association for Cancer cancerdiscovery.aacrjournals.org Downloaded from November 2014 CANCER DISCOVERY | 1267 views question surveys, reflecting the enthusiasm of the RAS community and the willingness of researchers to be engaged on their primary research topic. A key objective of the survey was to identify popular and interesting areas of research within the RAS community. Exciting developments reported by 2013 AACR Annual Meeting attendees involved resistance mechanisms to EGFR/ BRAF inhibitors, the role of wild-type RAS isoforms in KRASdriven tumors, and the intriguing dependency of KRASmutant models on activation for enhanced activity. In 2014, areas with promising achievements changed considerably as compared with previous years, with major interest in drug design for direct or indirect RAS targeting, preclinical– clinical translation with novel agents and combinations of targeted therapies in RAS/RAF–driven models, the role of oncogenic KRAS in metabolic reprogramming, and its interaction with the tumor microenvironment. Top publications in the field repeatedly mentioned by respondents reported the development of compounds that bind to well-defined surface pockets on oncogenic KRAS in a mutant-specific manner (2, 3) or that inhibit its interaction with plasma membrane/ scaffold proteins (4, 5). In line with these findings, in 2013, the most pressing question for RAS scientists concerned the druggability of KRAS, whereas in 2014, investigators were mainly interested in preclinical–clinical translation of KRASinteracting agents. We also asked attendees to revisit previous work in the RAS–RAF–MAPK domain and give an impartial opinion on areas of research that they consider oversaturated with repetitive findings or with results that are not reproducible. Many groups reported the failure to validate potential targets described in the literature as synthetic lethals in KRAS-mutant models as the major unexpected finding. Apart from high-throughput RNA interference screen studies, publications that attracted less attention from respondents in 2014 as compared with 2013 included those evaluating the preclinical activity of MEK inhibitors in combination with PI3K pathway inhibitors in KRAS-mutant models, resistance to selective BRAF inhibitors in melanoma, and genomesequencing studies assessing the molecular epidemiology of RAS/RAF. On the other hand, recurring topics with the highest interest for future research and that need more investment according to attendees were predominantly preclinical experiments linked to drug design and functional and systems biology approaches for studying MAPK pathway regulation in RAS-driven tumors. Most importantly, this exercise set the scene for the second part of the RAS interactome sessions, when we organized small group discussions, allowing similarly minded researchers to interact face to face. In these breakout sessions, tables of 10 to 15 people were set up, with placards at each table describing a subtopic within the RAS community, including “models of RAS,” “RAS regulators,” “metabolism,” “microenvironment,” “RAS drug targeting,” “preclinical–clinical translation,” and “clinical validation.” Attendees were asked to share their research questions and problems and to find areas where topic discussions and/or future collaborations could help resolve existing research bottlenecks. To understand the benefit of this breakout session, we sent out a follow-up survey after the conclusion of the 2014 AACR Annual Meeting. We received close to 50 responses, all of them reporting positively on the session and 11 describing new collaborations as a direct result of the breakout discussions. A common request was for greater structure within the discussion sections, with predefined leaders and more specialized topics of discussion. These comments reflected our own underappreciation of the desire for structured, albeit informal, discussions among conference attendees, and will be emphasized at future interactome sessions. FuTuRe oF BIomeDIcaL conFeRences The large attendance, enthusiastic response, and active participation by those at these AACR special sessions demonstrate a desire for alternative forms of interactions at biomedical conferences. Indeed, the need for roundtable dialogues engaging fellow scientists is a clear message of these experiments and should compel AACR and other organizations to expand this type of meeting to other areas. We therefore recommend the following components as important areas of attention for future conference planning.

Social Interactomes for Enabling Research Communities

Abstract: Summary: Data-driven analyses of scientific abstracts with web apps such as “abstract interactomes” provide a new visualization tool for the biomedical research community to interactively navigate a rich assembly of investigators and identify common research topics. Alternative conference formats such as “social interactomes,” with structured, albeit informal, discussions among attendees, are able to engage fellows and top investigators, facilitate the exchange of ideas, and encourage data sharing and future collaborations. Cancer Discov; 4(11); 1265–8. ©2014 AACR .