Literature DB >> 27084433

The Path(way) Less Traveled: A Pathway-Oriented Approach to Providing Information about Precision Cancer Medicine on My Cancer Genome.

Alexandria D Taylor1, Christine M Micheel2, Ingrid A Anderson1, Mia A Levy3, Christine M Lovly4.   

Abstract

This perspective describes the motivation, development, and implementation of pathway-based content for My Cancer Genome, an online precision medicine knowledge resource describing clinical implications of genetic alterations in cancer. As researchers uncover more about cancer pathogenesis, we are learning more not only about the specific genes and proteins involved but also about how those genes and proteins interact with others along cell signaling pathways. This knowledge has led researchers and clinicians to begin to think about cancer therapy using a pathway-based approach. To facilitate this approach, My Cancer Genome used a list of more than 800 cancer-related genes to identify 20 cancer-relevant pathways and then created content focused on demonstrating the therapeutic relevance of these pathways.
Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2016        PMID: 27084433      PMCID: PMC4833964          DOI: 10.1016/j.tranon.2016.03.001

Source DB:  PubMed          Journal:  Transl Oncol        ISSN: 1936-5233            Impact factor:   4.243


Precision medicine has altered the standard of care for cancer treatment and has led to the rapid development of therapies that inhibit diverse cellular processes. As we learn more about cancer pathogenesis, the number of plausible therapeutic targets increases. Targeted therapies have evolved from the use of single agents that inhibit a single gene effector to the use of one or more agents that target multiple effectors in a single cell signaling pathway or multiple effectors in parallel signaling pathways. As such, successful therapeutic strategies are evolving from a single-gene/single-drug focus to a pathway-based focus. This evolution of thought in targeted cancer therapy is an opportunity to develop a pathway-oriented view of cancer genomic knowledge resources. In response to this shift, the team at My Cancer Genome, http://www.mycancergenome.org/ [1], a project spearheaded at the Vanderbilt-Ingram Cancer Center, has developed a pathway-based approach to education and knowledge curation for precision cancer medicine. Targeted therapies revolutionized cancer medicine by enabling disease control in traditionally difficult to treat malignancies, such as BRAF-mutated melanoma, by targeting the mutated gene with a single inhibitor. As knowledge of cancer pathogenesis advanced, the number of targeted therapies rapidly increased—making it essential to understand the complex signaling networks through which altered genes function and interact to contribute to disease. Understanding these signaling pathways will facilitate the creation of rational combination therapies for cancer patients with the ultimate goal of increasing the depth and duration of response. Two approaches to pathway-based treatment strategies are vertical and parallel inhibition. To understand vertical inhibition, consider BRAF-mutated melanoma. Single-agent BRAF inhibition induced response rates in 53% of patients with BRAF-mutated melanoma [2]; however, acquired resistance invariably developed in these tumors. This therapeutic escape created a problem: how could clinicians extend the drug response and delay or overcome acquired resistance? The solution depends on understanding the complex interactions BRAF maintains with other proteins in a cancer cell. By combining BRAF with MEK inhibitors, two targets in the same pathway, clinicians can extend the drug response [3]. This method of targeted cancer therapy is known as vertical inhibition—simultaneously targeting multiple proteins with multiple inhibitors within the same signaling pathway. With vertical inhibition, clinicians may create stronger, on-target inhibition of nodes in the same pathway. To understand parallel inhibition, consider the example of ER + breast cancer. In 2012, the aromatase inhibitor exemestane was FDA approved for use in combination with mTOR inhibitor everolimus for patients with ER + metastatic breast cancer [4]. Exemestane targets the hormone signaling pathway, whereas everolimus targets the PI3K/AKT1/mTOR pathway. In 2015, the aromatase inhibitor letrozole was FDA approved for use in combination with CDK4/6 inhibitor palbociclib for postmenopausal patients with ER +, HER2-negative advanced breast cancer [5]. Letrozole targets the hormone signaling pathway, whereas palbociclib targets the cell cycle. This method of targeted cancer therapy is known as parallel inhibition—simultaneously targeting multiple nodes in different cell signaling pathways. Currently available resources can provide a seemingly overwhelming amount of information regarding the complex entanglement of upstream, downstream, and parallel signaling pathways involved in the cellular circuitry. The complexity may make it difficult and time consuming for a busy clinician to search for a given protein target of interest. Furthermore, currently available resources may not be able to easily connect the pathway information to information directly pertaining to the therapeutic strategies. The team at My Cancer Genome recognizes that keeping up with the rapid development of targeted therapies amidst a busy clinical schedule is challenging; therefore, the team has restructured typical complex signaling pathways to be more digestible to clinicians in practice. The goal was to create a resource from which a clinician would be able to quickly glean the information necessary to understand the significance of an individual pathway that drives cancer pathogenesis or a therapeutic strategy within the context of precision cancer medicine. The creation of a pathway-based resource for genomic information reflects the emergence of combination therapies used in current cancer treatment. The methodology behind the creation of the pathway content focused on ease of understanding while maintaining clinical relevance; the team aimed to create pathway diagrams that were clinically applicable, gearing the level of information toward clinicians in practice. This involved working with the My Cancer Genome editorial team to outline a map of the most cancer-relevant pathways (Figure 1) [6]. We then categorized a master list of approximately 820 cancer-related genes [7] compiled from several commonly used next-generation sequencing cancer platforms. From there, we created diagrams that were isolated from surrounding pathway interactions. Each diagram included the most relevant proteins in each pathway with a focus on therapeutic targets. Descriptive text that defined each pathway’s function, activators, inhibitors, and cellular outputs was created to accompany the pathway diagram. Each figure includes a pathway summary describing the components of the pathway, diseases in which the pathway is aberrantly activated, and a drug list—all of which link to more detailed information where available on the My Cancer Genome website.
Figure 1

Cancer-relevant pathway map. This figure depicts the names of the most cancer-relevant pathways on My Cancer Genome and their sites of action within the tumor cell. For example, the G-protein signaling pathway commences at the cell membrane and then transduces downstream signals within the tumor cell. Individual pathway figures for each cell signaling pathway can be found on the My Cancer Genome website at http://www.MyCancerGenome.org/content/pathways[6]. Reprinted, with permission, from My Cancer Genome. Copyright 2016 Vanderbilt University.

A single-gene to single-drug approach was once the most effective strategy in cancer medicine. However, diagnostic tools and cancer therapies continue to advance, as do complex cancer mechanisms. With the capability to identify multiple mutations within a tumor, clinicians will benefit from understanding why and how to effectively inhibit multiple, co-occurring genomic alterations within the tumor. A pathway-based approach to cancer medicine may help clinicians find answers to hard questions: Are the alterations related? Which genes do the altered genes interact with? Are the alterations targetable? If so, do drugs exist that can effectively inhibit each alteration? A pathway-based approach also creates an opportunity to explore rational combination strategies that will target not only the tumor but also the tumor microenvironment and surrounding immune system. With the new pathway-based approach to education and knowledge curation, My Cancer Genome hopes that the path(way) less traveled will positively impact patient care using precision cancer medicine.
  2 in total

1.  Improved overall survival in melanoma with combined dabrafenib and trametinib.

Authors:  Caroline Robert; Boguslawa Karaszewska; Jacob Schachter; Piotr Rutkowski; Andrzej Mackiewicz; Daniil Stroiakovski; Michael Lichinitser; Reinhard Dummer; Florent Grange; Laurent Mortier; Vanna Chiarion-Sileni; Kamil Drucis; Ivana Krajsova; Axel Hauschild; Paul Lorigan; Pascal Wolter; Georgina V Long; Keith Flaherty; Paul Nathan; Antoni Ribas; Anne-Marie Martin; Peng Sun; Wendy Crist; Jeff Legos; Stephen D Rubin; Shonda M Little; Dirk Schadendorf
Journal:  N Engl J Med       Date:  2014-11-16       Impact factor: 91.245

2.  Combined BRAF and MEK inhibition in melanoma with BRAF V600 mutations.

Authors:  Keith T Flaherty; Jeffery R Infante; Adil Daud; Rene Gonzalez; Richard F Kefford; Jeffrey Sosman; Omid Hamid; Lynn Schuchter; Jonathan Cebon; Nageatte Ibrahim; Ragini Kudchadkar; Howard A Burris; Gerald Falchook; Alain Algazi; Karl Lewis; Georgina V Long; Igor Puzanov; Peter Lebowitz; Ajay Singh; Shonda Little; Peng Sun; Alicia Allred; Daniele Ouellet; Kevin B Kim; Kiran Patel; Jeffrey Weber
Journal:  N Engl J Med       Date:  2012-09-29       Impact factor: 91.245

  2 in total
  18 in total

1.  Clinical Applications of Next-Generation Sequencing in Precision Oncology.

Authors:  Chris A Karlovich; P Mickey Williams
Journal:  Cancer J       Date:  2019 Jul/Aug       Impact factor: 3.360

2.  Toward Molecularly Driven Precision Medicine in Lung Adenocarcinoma.

Authors:  David Liu; Natalie I Vokes; Eliezer M Van Allen
Journal:  Cancer Discov       Date:  2017-06       Impact factor: 39.397

3.  Pathway Analysis for Cancer Research and Precision Oncology Applications.

Authors:  Alessandro La Ferlita; Salvatore Alaimo; Alfredo Ferro; Alfredo Pulvirenti
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

4.  Comparison of Annotation Services for Next-Generation Sequencing in a Large-Scale Precision Oncology Program.

Authors:  Evangelia Katsoulakis; Jill E Duffy; Bradley Hintze; Neil L Spector; Michael J Kelley
Journal:  JCO Precis Oncol       Date:  2020-03-24

Review 5.  Limitations and opportunities of technologies for the analysis of cell-free DNA in cancer diagnostics.

Authors:  Ping Song; Lucia Ruojia Wu; Yan Helen Yan; Jinny X Zhang; Tianqing Chu; Lawrence N Kwong; Abhijit A Patel; David Yu Zhang
Journal:  Nat Biomed Eng       Date:  2022-01-31       Impact factor: 29.234

6.  Somatic cancer variant curation and harmonization through consensus minimum variant level data.

Authors:  Deborah I Ritter; Sameek Roychowdhury; Angshumoy Roy; Shruti Rao; Melissa J Landrum; Dmitriy Sonkin; Mamatha Shekar; Caleb F Davis; Reece K Hart; Christine Micheel; Meredith Weaver; Eliezer M Van Allen; Donald W Parsons; Howard L McLeod; Michael S Watson; Sharon E Plon; Shashikant Kulkarni; Subha Madhavan
Journal:  Genome Med       Date:  2016-11-04       Impact factor: 11.117

Review 7.  Integrating cancer genomic data into electronic health records.

Authors:  Jeremy L Warner; Sandeep K Jain; Mia A Levy
Journal:  Genome Med       Date:  2016-10-26       Impact factor: 11.117

8.  EGFR mutations are associated with response to depatux-m in combination with temozolomide and result in a receptor that is hypersensitive to ligand.

Authors:  Youri Hoogstrate; Wies Vallentgoed; Johan M Kros; Iris de Heer; Maurice de Wit; Marica Eoli; Juan Manuel Sepulveda; Annemiek M E Walenkamp; Jean-Sebastien Frenel; Enrico Franceschi; Paul M Clement; Micheal Weller; Martin E van Royen; Peter Ansell; Jim Looman; Earle Bain; Marie Morfouace; Thierry Gorlia; Vassilis Golfinopoulos; Martin van den Bent; Pim J French
Journal:  Neurooncol Adv       Date:  2019-12-09

9.  Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology.

Authors:  Frank P Lin; Subotheni Thavaneswaran; John P Grady; Mandy Ballinger; Maya Kansara; Samantha R Oakes; Jayesh Desai; Chee Khoon Lee; John Simes; David M Thomas
Journal:  NPJ Precis Oncol       Date:  2021-06-23

10.  An integrated clinical and genomic information system for cancer precision medicine.

Authors:  Yeongjun Jang; Taekjin Choi; Jongho Kim; Jisub Park; Jihae Seo; Sangok Kim; Yeajee Kwon; Seungjae Lee; Sanghyuk Lee
Journal:  BMC Med Genomics       Date:  2018-04-20       Impact factor: 3.063

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.