| Literature DB >> 34208794 |
Lauren K Jillson1, Gabriel A Yette1, Teemu D Laajala1,2, Wayne D Tilley3,4, James C Costello1, Scott D Cramer1.
Abstract
While many prostate cancer (PCa) cases remain indolent and treatable, others are aggressive and progress to the metastatic stage where there are limited curative therapies. Androgen receptor (AR) signaling remains an important pathway for proliferative and survival programs in PCa, making disruption of AR signaling a viable therapy option. However, most patients develop resistance to AR-targeted therapies or inherently never respond. The field has turned to PCa genomics to aid in stratifying high risk patients, and to better understand the mechanisms driving aggressive PCa and therapy resistance. While alterations to the AR gene itself occur at later stages, genomic changes at the primary stage can affect the AR axis and impact response to AR-directed therapies. Here, we review common genomic alterations in primary PCa and their influence on AR function and activity. Through a meta-analysis of multiple independent primary PCa databases, we also identified subtypes of significantly co-occurring alterations and examined their combinatorial effects on the AR axis. Further, we discussed the subsequent implications for response to AR-targeted therapies and other treatments. We identified multiple primary PCa genomic subtypes, and given their differing effects on AR activity, patient tumor genetics may be an important stratifying factor for AR therapy resistance.Entities:
Keywords: AR; Androgen receptor; genomics; hormone receptor; lineage plasticity; prostate cancer; resistance; subtype; therapy
Year: 2021 PMID: 34208794 PMCID: PMC8269091 DOI: 10.3390/cancers13133272
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1Genomic alterations across multiple primary PCa cohorts. Meta-analysis of three independent cohorts of primary PCa evaluating frequencies of the most common genomic alterations at this disease stage: TCGA [21], MSKCC [15], and BROAD [22]. The MSKCC dataset had few samples with mutation data, so mutational frequencies are underrepresented in this cohort. Shallow and deep deletions indicate heterozygous and homozygous deletions, respectively. Gain and amplification indicate low-level and high-level copy gain, respectively. Calls for alterations are based on algorithms used and parameters set within each cohort’s data repository.
Figure 2AR activity across primary PCa genomic subtypes. (a) Normalized AR-score values for patients with each indicated alteration in the TCGA and MSKCC cohorts. (b) Normalized AR mRNA reads for patients with each indicated alteration in the TCGA cohort. (c) AR Score values for subgroups of patients in the TCGA and MSKCC cohorts that contain the alterations listed versus patients that contain none of the alterations listed. (d) Normalized AR mRNA reads for subgroups of patients that contain the alterations listed versus patients that contain none of the alterations listed. All data points represent medians (point) with interquartile range (lines). The dotted line is the average across all patients in the cohort. Only available alterations or subgroups with at least 5 patients were included in analyses. Mann-Whitney test; * p < 0.01, *** p < 0.0001, **** p < 0.00001, ns = not significant.
Co-occurrence and mutual exclusivity of alterations in the TCGA cohort.
| Subtype | A | B | Neither | A Not B | B Not A | Both | Log2 Odds Ratio | Tendency | ||
|---|---|---|---|---|---|---|---|---|---|---|
| 203 | 76 | 12 | 42 | >3 | <0.001 | <0.001 | Co-occurrence | |||
| 210 | 88 | 5 | 30 | >3 | <0.001 | <0.001 | Co-occurrence | |||
| 272 | 26 | 7 | 28 | >3 | <0.001 | <0.001 | Co-occurrence | |||
| 180 | 35 | 83 | 35 | 1.117 | 0.004 | 0.017 | Co-occurrence | |||
| 264 | 45 | 15 | 9 | 1.816 | 0.007 | 0.033 | Co-occurrence | |||
| 209 | 100 | 6 | 18 | 2.648 | <0.001 | <0.001 | Co-occurrence | |||
| Exclusive from | 92 | 123 | 89 | 29 | −2.037 | <0.001 | <0.001 | Mutual exclusivity | ||
| 153 | 151 | 28 | 1 | <−3 | <0.001 | <0.001 | Mutual exclusivity | |||
| 135 | 144 | 46 | 8 | −2.617 | <0.001 | <0.001 | Mutual exclusivity | |||
| 158 | 151 | 23 | 1 | <−3 | <0.001 | <0.001 | Mutual exclusivity | |||
| 168 | 152 | 13 | 0 | <−3 | <0.001 | 0.002 | Mutual exclusivity | |||
| 115 | 123 | 66 | 29 | −1.283 | <0.001 | 0.002 | Mutual exclusivity | |||
| 167 | 150 | 14 | 2 | −2.652 | 0.005 | 0.022 | Mutual exclusivity | |||
| 146 | 152 | 35 | 0 | <−3 | <0.001 | <0.001 | Mutual exclusivity | |||
| Exclusive from | 194 | 104 | 34 | 1 | <−3 | <0.001 | <0.001 | Mutual exclusivity | ||
| 207 | 91 | 33 | 2 | −2.859 | <0.001 | 0.004 | Mutual exclusivity | |||
| 260 | 35 | 38 | 0 | <−3 | 0.011 | 0.045 | Mutual exclusivity | |||
| 151 | 89 | 30 | 63 | 1.833 | <0.001 | <0.001 | Co-occurrence | |||
| 181 | 47 | 59 | 46 | 1.586 | <0.001 | <0.001 | Co-occurrence | |||
| 141 | 87 | 40 | 65 | 1.397 | <0.001 | <0.001 | Co-occurrence | |||
| 206 | 68 | 34 | 25 | 1.155 | 0.006 | 0.028 | Co-occurrence | |||
| 285 | 17 | 24 | 7 | 2.29 | 0.003 | 0.017 | Co-occurrence | |||
| 220 | 54 | 21 | 38 | 2.882 | <0.001 | <0.001 | Co-occurrence | |||
| 218 | 61 | 23 | 31 | 2.268 | <0.001 | <0.001 | Co-occurrence | |||
| 224 | 74 | 17 | 18 | 1.68 | 0.001 | 0.008 | Co-occurrence | |||
|
| 201 | 27 | 74 | 31 | 1.641 | <0.001 | <0.001 | Co-occurrence | ||
| 270 | 50 | 5 | 8 | >3 | <0.001 | 0.002 | Co-occurrence | |||
| 188 | 27 | 87 | 31 | 1.311 | 0.002 | 0.009 | Co-occurrence | |||
| 252 | 46 | 23 | 12 | 1.515 | 0.008 | 0.036 | Co-occurrence | |||
| 237 | 42 | 38 | 16 | 1.248 | 0.011 | 0.045 | Co-occurrence | |||
|
| 294 | 8 | 26 | 5 | 2.821 | 0.004 | 0.018 | Co-occurrence | ||
| 300 | 9 | 20 | 4 | 2.737 | 0.01 | 0.04 | Co-occurrence | |||
| 274 | 46 | 5 | 8 | >3 | <0.001 | 0.002 | Co-occurrence | |||
| 211 | 109 | 4 | 9 | 2.123 | 0.012 | 0.047 | Co-occurrence | |||
| 237 | 83 | 4 | 9 | 2.684 | 0.002 | 0.01 | Co-occurrence | |||
|
| 219 | 76 | 19 | 19 | 1.527 | 0.002 | 0.013 | Co-occurrence | ||
| 212 | 62 | 26 | 33 | 2.118 | <0.001 | <0.001 | Co-occurrence | |||
| 224 | 78 | 14 | 17 | 1.802 | 0.001 | 0.007 | Co-occurrence | |||
| 209 | 29 | 70 | 25 | 1.364 | 0.002 | 0.01 | Co-occurrence | |||
| 169 | 69 | 46 | 49 | 1.384 | <0.001 | <0.001 | Co-occurrence | |||
| 213 | 25 | 62 | 33 | 2.181 | <0.001 | <0.001 | Co-occurrence | |||
| 185 | 53 | 56 | 39 | 1.282 | <0.001 | 0.004 | Co-occurrence | |||
| 178 | 60 | 50 | 45 | 1.417 | <0.001 | <0.001 | Co-occurrence |
Statistical analysis for trends of co-occurrence and mutual exclusivity between all pairwise comparisons of genomic alterations in the TCGA cohort. Only statistically significant trends are included. Significant genomic subtypes, based on alteration co-occurrences, are highlighted in orange, and alterations that occur across multiple subtypes are shown in gray. Alterations that are mutually exclusive from one another are shown in blue.