Lund-Andersen Christin, Torgunrud Annette, Fleten Karianne Giller, Flatmark Kjersti
Department of Tumor Biology, Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway.
Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
J Gastrointest Oncol. 2021 Apr;12(Suppl 1):S191-S203. doi: 10.21037/jgo-20-136.
High-throughput "-omics" analysis may provide a broader and deeper understanding of cancer biology to define prognostic and predictive biomarkers and identify novel therapy targets. In this review we provide an overview of studies where the peritoneal tumor component of peritoneal metastases from colorectal cancer (PM-CRC) and pseudomyxoma peritonei (PMP) were analyzed. Most of the available data was derived from DNA mutation analysis, but a brief review of findings from transcriptomic and protein expression analysis was also performed. Studies reporting genomic analysis of peritoneal tumor samples from 1,779 PM-CRC and 623 PMP cases were identified. The most frequently mutated genes in PM-CRC were , , , , and , while in PMP , , , , and mutations were most commonly identified. Analyses were performed by single-gene analyses and to some extent targeted next-generation sequencing, and a very limited amount of broad explorative data exists. The investigated cohorts were typically small and heterogeneous with respect to the methods used and to the reporting of clinical data. This was even more apparent regarding transcriptomic and protein data, as the low number of cases examined and quality of clinical data would not support firm conclusions. Even for the most frequently mutated genes, the results varied greatly; for instance, mutations were reported at frequencies between 20-57% in PM-CRC and 38-100% in PMP. Such variation could be caused by random effects in small cohorts, heterogeneity in patient selection, or sensitivity of applied technology. Although a large number of samples have been subjected to analysis, cross-study comparisons are difficult to perform, and combined with small cohorts and varying quality and detail of clinical information, the observed variation precludes useful interpretation in a clinical context. Although omics data in theory could answer questions to aid management decisions in PM-CRC and PMP, the existing data does not presently support clinical implementation. With the necessary technologies being generally available, the main challenge will be to obtain sufficiently large, representative cohorts with adequate clinical data and standardized reporting of results. Importantly, studies where the focus is specifically on peritoneal disease are needed, where the study designs are aligned with clearly defined research questions to allow robust conclusions. Such studies are highly warranted if patients with PM-CRC and PMP are to derive benefit from recent advances in precision cancer medicine.
高通量“组学”分析可能会为癌症生物学提供更广泛、更深入的理解,以定义预后和预测生物标志物,并识别新的治疗靶点。在本综述中,我们概述了对结直肠癌腹膜转移(PM-CRC)和腹膜假黏液瘤(PMP)的腹膜肿瘤成分进行分析的研究。现有数据大多来自DNA突变分析,但也对转录组学和蛋白质表达分析的结果进行了简要综述。我们确定了报告对1779例PM-CRC和623例PMP病例的腹膜肿瘤样本进行基因组分析的研究。PM-CRC中最常发生突变的基因是 、 、 、 和 ,而在PMP中, 、 、 、 和 突变最为常见。分析通过单基因分析以及在一定程度上通过靶向新一代测序进行,且存在的广泛探索性数据非常有限。所研究的队列通常规模较小,在使用的方法和临床数据报告方面存在异质性。对于转录组学和蛋白质数据而言,这种情况更为明显,因为所检查的病例数量较少且临床数据质量不支持得出确凿结论。即使对于最常发生突变的基因,结果也差异很大;例如, 在PM-CRC中的报告频率为20%-57%,在PMP中的报告频率为38%-100%。这种差异可能是由小队列中的随机效应、患者选择的异质性或应用技术的敏感性导致的。尽管已经对大量样本进行了分析,但跨研究比较难以进行,再加上队列规模小以及临床信息的质量和细节各不相同,观察到的差异使得在临床背景下难以进行有用的解读。虽然组学数据理论上可以回答有助于PM-CRC和PMP管理决策的问题,但现有数据目前不支持临床应用。由于必要的技术普遍可用,主要挑战将是获得足够大的、具有代表性的队列,并具备充分的临床数据和标准化的结果报告。重要的是,需要开展专门聚焦于腹膜疾病的研究,其研究设计要与明确界定清晰的研究问题保持一致,以便得出可靠的结论。如果PM-CRC和PMP患者要从精准癌症医学的最新进展中获益,此类研究非常有必要。