Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012;7(12):e50141.
doi: 10.1371/journal.pone.0050141. Epub 2012 Dec 10.

Oligo- and polymetastatic progression in lung metastasis(es) patients is associated with specific microRNAs

Affiliations

Oligo- and polymetastatic progression in lung metastasis(es) patients is associated with specific microRNAs

Yves A Lussier et al. PLoS One. 2012.

Erratum in

  • PLoS One. 2013;8(6). doi: 10.1371/annotation/2489ae5e-3650-4897-8df6-3e974ca585c4. Gnerlich, Jennifer [corrected to Gnerlich, Jennifer L]

Abstract

Rationale: Strategies to stage and treat cancer rely on a presumption of either localized or widespread metastatic disease. An intermediate state of metastasis termed oligometastasis(es) characterized by limited progression has been proposed. Oligometastases are amenable to treatment by surgical resection or radiotherapy.

Methods: We analyzed microRNA expression patterns from lung metastasis samples of patients with ≤ 5 initial metastases resected with curative intent.

Results: Patients were stratified into subgroups based on their rate of metastatic progression. We prioritized microRNAs between patients with the highest and lowest rates of recurrence. We designated these as high rate of progression (HRP) and low rate of progression (LRP); the latter group included patients with no recurrences. The prioritized microRNAs distinguished HRP from LRP and were associated with rate of metastatic progression and survival in an independent validation dataset.

Conclusion: Oligo- and poly- metastasis are distinct entities at the clinical and molecular level.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Stratification of metastatic phenotypes in lung metastasis patient samples reveals three distinct subgroups and a difference in survival outcome between patients with high vs. low rates of progression.
A, lung metastasis patients were stratified according to the time (years) to first recurrent metastasis following pulmonary metastectomy (x-axis) and rate of recurrent metastases (per year) over follow-up after surgery (y-axis). Three distinct subgroups emerged using cutoffs for the rate of recurrent metastases: patients with a high rate of progression develop at least 3.6 new tumors/year after surgery and tend to exhibit their first recurrence in the first year following surgery (HRP, red circles); patients with a low rate of progression develop less than 0.6 new tumors/year after surgery (LRP, blue circles); remaining patients that do not meet the criteria for high or low rate of progression status are classified with an intermediate rate of progression (IRP, white circles). Green dotted lines represent the aforementioned rate thresholds. LRP patients exhibiting no recurrence after metastectomy were also plotted here for convenience as yielding 0.0 metastases/month on the y-axis. See Tables S1 and S2 for further clinical information. B, lung metastasis patients of the LRP (n = 32) and HRP (n = 16) subgroups were compared for their survival outcome using log-rank Mantel-Cox analysis. The median survival of LRP and HRP patients is 63.5 months and 18 months, respectively. A log-rank Mantel-Cox p<0.0001 was obtained when comparing LRP vs. HRP survival outcome.
Figure 2
Figure 2. Unsupervised hierarchical clustering of microRNAs derived from lung metastasis samples distinguishes patients with high vs. low rates of metastatic progression.
Expression of 384 microRNAs in metastatic lung tumor samples above, at, and below mean level are represented by red, black, and green TaqMan qPCR Ct values across all patients (n = 63) and were used to cluster oligo- and poly-metastatic patients. As shown above, 13 of 16 HRP patients (red on color-coded bar above the dendrogram) cluster together (left dendrogram branch) and 20 of 32 LRP patients (blue color-coded bar) cluster together from these HRP patients (right dendrogram branch), resulting in a divergence of these diametric sub-phenotypes (odds ratio = 7.22; Fisher's Exact Test, two-tailed p = 0.006). We also observed significant differences between patients classified as polymetastatic (P) vs. oligometastatic (O) (OR = 3.89, FET p = 0.019; Methods).
Figure 3
Figure 3. Rate of metastasis progression of patients in an independent validation dataset are associated to prioritized microRNAs discovered in patients with high vs. low rates of progression discovered in the lung metastasis dataset.
A, patients of the independent validation dataset are stratified as described in Figure 1 according to a high rate of progression (HRP, red circles), low rate of progression (LRP, blue circles), and intermediate rate of progression (IRP, white circles). Green dotted lines represent rate thresholds. LRP patients exhibiting no recurrence after radiation therapy were also plotted as yielding 0 metastases/month on the y-axis. Of note, all HRP patients exhibit polymetastatic progression, all LRP patients exhibit oligometastatic progression, and IRP patients represent patients with oligometastatic progression that do not meet the LRP criteria (Methods). See Table S3 for patient classification into metastatic progression groups in the independent validation dataset. B, Patients of the LRP (n = 10) and HRP (n = 14) subgroups from dataset GSE25552 were compared for their survival outcome using log-rank Mantel-Cox analysis. The median survival of LRP and HRP patients is 26 months and 12 months, respectively. A log-rank Mantel Cox p<0.0022 was obtained when comparing LRP vs. HRP survival outcome. C. microRNAs differentially expressed in HRP and LRP patients from the lung metastases samples stratify patients in independent dataset GSE25552. 8 of 10 LRP patients cluster together (left branch) and 9 of 14 HRP patients cluster separately from these LRP patients (right branch), resulting in a divergence of these metastatic phenotypes (odds ratio = 7.2; Fisher's Exact Test, two-tailed p = 0.047). Color-coded designations-see Figure 1 .
Figure 4
Figure 4. Lung oligometastatic and polymetastatic progression samples are differentiated through hierarchical clustering with prioritized microRNA features derived from the independent validation dataset GSE25552.
29 microRNAs differentially expressed between polymetastatic vs. oligometastatic progression (GSE25552) were used to stratify lung metastatic samples, described in the current report (n = 63) . As shown above, 17 of 39 oligometastatic progression patients cluster together (left branch) and 20 of 24 polymetastatic progression patients cluster separately (right branch; odds ratio = 3.86; Fisher's Exact Test, two-tailed p = 0.032; Methods). See Methods for definitions of polymetastatic and oligometastatic progression.

Similar articles

Cited by

References

    1. Siegel R, Naishadham D, Jemal A (2012) Cancer statistics, 2012. CA Cancer J Clin 62: 10–29. - PubMed
    1. Williams SD, Birch R, Einhorn LH, Irwin L, Greco FA, et al. (1987) Treatment of disseminated germ-cell tumors with cisplatin, bleomycin, and either vinblastine or etoposide. N Engl J Med 316: 1435–1440. - PubMed
    1. Saxman SB, Finch D, Gonin R, Einhorn LH (1998) Long-term follow-up of a phase III study of three versus four cycles of bleomycin, etoposide, and cisplatin in favorable-prognosis germ-cell tumors: the Indian University experience. J Clin Oncol 16: 702–706. - PubMed
    1. Hellman S, Weichselbaum RR (1995) Oligometastases. J Clin Oncol 13: 8–10. - PubMed
    1. Weichselbaum RR, Hellman S (2011) Oligometastases revisited. Nat Rev Clin Oncol 8: 378–382. - PubMed

Publication types

Associated data

  NODES
Note 1
Project 1
twitter 2