ALAN is a computational approach that interprets genomic findings in the context of tumor ecosystems

Hannah E Bergom; Ashraf Shabaneh; Abderrahman Day; Atef Ali; Ella Boytim; Sydney Tape; John R Lozada; Xiaolei Shi; Carlos Perez Kerkvliet; Sean McSweeney; Samuel P Pitzen; Megan Ludwig; Emmanuel S Antonarakis; Justin M Drake; Scott M Dehm; Charles J Ryan; Jinhua Wang; Justin Hwang

doi:10.1038/s42003-023-04795-1

ALAN is a computational approach that interprets genomic findings in the context of tumor ecosystems

Commun Biol. 2023 Apr 14;6(1):417. doi: 10.1038/s42003-023-04795-1.

Authors

Hannah E Bergom^#^{1

2}, Ashraf Shabaneh^#^{1

3}, Abderrahman Day^#^{1

2

3}, Atef Ali^{1

2}, Ella Boytim^{1

2}, Sydney Tape^{1

2}, John R Lozada¹, Xiaolei Shi¹, Carlos Perez Kerkvliet¹, Sean McSweeney¹, Samuel P Pitzen^{4

5}, Megan Ludwig⁶, Emmanuel S Antonarakis^{1

2

4}, Justin M Drake^{1

6

7}, Scott M Dehm^{4

7

8}, Charles J Ryan^{1

2

4

9}, Jinhua Wang^{1

3

4}, Justin Hwang^{10

11

12}

Affiliations

¹ Department of Medicine, University of Minnesota Masonic Cancer Center, Minneapolis, MN, USA.
² Division of Hematology, Oncology and Transplantation, University of Minnesota, Minneapolis, MN, USA.
³ Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
⁴ Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
⁵ Graduate Program in Molecular, Cellular, and Developmental Biology and Genetics, University of Minnesota, Minneapolis, MN, USA.
⁶ Department of Pharmacology, University of Minnesota, Minneapolis, MN, USA.
⁷ Department of Urology, University of Minnesota, Minneapolis, MN, USA.
⁸ Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
⁹ Prostate Cancer Foundation, Santa Monica, CA, USA.
¹⁰ Department of Medicine, University of Minnesota Masonic Cancer Center, Minneapolis, MN, USA. jhwang@umn.edu.
¹¹ Division of Hematology, Oncology and Transplantation, University of Minnesota, Minneapolis, MN, USA. jhwang@umn.edu.
¹² Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA. jhwang@umn.edu.

^# Contributed equally.

Abstract

Gene behavior is governed by activity of other genes in an ecosystem as well as context-specific cues including cell type, microenvironment, and prior exposure to therapy. Here, we developed the Algorithm for Linking Activity Networks (ALAN) to compare gene behavior purely based on patient -omic data. The types of gene behaviors identifiable by ALAN include co-regulators of a signaling pathway, protein-protein interactions, or any set of genes that function similarly. ALAN identified direct protein-protein interactions in prostate cancer (AR, HOXB13, and FOXA1). We found differential and complex ALAN networks associated with the proto-oncogene MYC as prostate tumors develop and become metastatic, between different cancer types, and within cancer subtypes. We discovered that resistant genes in prostate cancer shared an ALAN ecosystem and activated similar oncogenic signaling pathways. Altogether, ALAN represents an informatics approach for developing gene signatures, identifying gene targets, and interpreting mechanisms of progression or therapy resistance.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Ecosystem*
Genes, myc
Genomics
Humans
Male
Prostatic Neoplasms* / pathology
Signal Transduction / genetics
Tumor Microenvironment / genetics

Abstract

Publication types

MeSH terms

Grants and funding