Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Urologic Oncology Program & Uro-Oncology Research Program, Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Prostate Cancer Prostatic Dis. 2021 Sep;24(3):733-742. doi: 10.1038/s41391-021-00325-4. Epub 2021 Feb 2.
Two prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the "Prostate Cancer Classification System" (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most human PC can be assigned to one of three tumor subtypes, two categorized as luminal and one as basal, suggesting the two methods reflect consistency in underlying biology. Despite the similarity, differences and commonalities between the two classification methods have not yet been reported.
Here, we describe a comparison of the PCS and PAM50 classification systems. PCS and PAM50 signatures consisting of 37 (PCS37) and 50 genes, respectively, were used to categorize 9,947 PC patients into PCS and PAM50 classes. Enrichment of hallmark gene sets and luminal and basal marker gene expression were assessed in the same datasets. Finally, survival analysis was performed to compare PCS and PAM50 subtypes in terms of clinical outcomes.
PCS and PAM50 subtypes show clear differential expression of PCS37 and PAM50 genes. While only three genes are shared in common between the two systems, there is some consensus between three subtype pairs (PCS1 versus Luminal B, PCS2 versus Luminal A, and PCS3 versus Basal) with respect to gene expression, cellular processes, and clinical outcomes. PCS categories displayed better separation of cellular processes and luminal and basal marker gene expression compared to PAM50. Although both PCS1 and Luminal B tumors exhibited the worst clinical outcomes, outcomes between aggressive and less aggressive subtypes were better defined in the PCS system, based on larger hazard ratios observed.
The PCS and PAM50 classification systems are similar in terms of molecular profiles and clinical outcomes. However, the PCS system exhibits greater separation in multiple clinical outcomes and provides better separation of prostate luminal and basal characteristics.
最近提出了两种基于转录组谱的前列腺癌 (PC) 分类方法,一种是新提出的“前列腺癌分类系统”(PCS),另一种是改良的 PAM50 乳腺癌算法。这两项研究都得出结论,大多数人类 PC 可以分为三种肿瘤亚型,两种归类为 luminal,一种归类为基底,这表明这两种方法反映了潜在生物学的一致性。尽管这两种分类方法相似,但它们之间的差异和共同点尚未得到报道。
在这里,我们描述了 PCS 和 PAM50 分类系统的比较。使用分别包含 37 个基因(PCS37)和 50 个基因的 PCS 和 PAM50 特征,将 9947 名 PC 患者分为 PCS 和 PAM50 类别。在相同的数据集上评估了标志性基因集和 luminal 和基底标记基因表达的富集情况。最后,进行了生存分析,以比较 PCS 和 PAM50 亚型在临床结果方面的差异。
PCS 和 PAM50 亚型显示 PCS37 和 PAM50 基因的表达存在明显差异。虽然两个系统共有三个共同基因,但在三个亚型对(PCS1 与 Luminal B、PCS2 与 Luminal A 和 PCS3 与 Basal)之间,基因表达、细胞过程和临床结果存在一些共识。与 PAM50 相比,PCS 类别在细胞过程和 luminal 和基底标记基因表达方面显示出更好的分离。尽管 PCS1 和 Luminal B 肿瘤的临床结果最差,但基于观察到的更大风险比,PCS 系统在更具侵袭性和侵袭性较小的亚型之间的临床结果定义更好。
在分子谱和临床结果方面,PCS 和 PAM50 分类系统相似。然而,PCS 系统在多个临床结果中表现出更好的分离,并且提供了更好的前列腺 luminal 和基底特征分离。