The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index; 4 of the 7 sources its claims cite were checked for support.
Blood Cell Origin of Circulating MicroRNAs: A Cautionary Note for Cancer Biomarker Studies
Open accessPublished version of a preprint
Abstract
Circulating, cell-free microRNAs (miRNAs) hold great promise as a new class of cancer biomarkers due to their surprisingly high stability in plasma, association with disease states, and ease of sensitive measurement. Yet little is known about the origin of circulating miRNAs in either healthy or sick people or what factors influence levels of circulating miRNA biomarkers. Of 79 solid tumor circulating miRNA biomarkers reported in the literature, we found that 58% (46 of 79) are highly expressed in one or more blood cell type. Plasma levels of miRNA biomarkers expressed by myeloid (e.g., miR-223, miR-197, miR-574-3p, and let-7a) and lymphoid (e.g., miR-150) blood cells tightly correlated with corresponding white blood cell counts. Plasma miRNA biomarkers expressed by red blood cells (e.g., miR-486-5p, miR-451, miR-92a, and miR-16) could not be correlated to red cell counts due to limited variation in hematocrit in the cohort studied but were significantly increased in hemolyzed specimens (20- to 30-fold plasma increase; P < 0.0000001). Finally, in a patient undergoing autologous hematopoietic cell transplantation, plasma levels of myeloid- and lymphoid-expressed miRNAs (miR-223 and miR-150, respectively) tracked closely with changes in corresponding blood counts. We present evidence that blood cells are a major contributor to circulating miRNA and that perturbations in blood cell counts and hemolysis can alter plasma miRNA biomarker levels by up to 50-fold. Given that a majority of reported circulating miRNA cancer biomarkers are highly expressed in blood cells, we suggest caution in interpretation of such results as they may reflect a blood cell-based phenomenon rather than a cancer-specific origin. Cancer Prev Res; 5(3); 492–7. ©2011 AACR.
Overview
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Written from the paper’s full text.
TL;DR
Circulating microRNA biomarkers for solid tumors are frequently expressed by blood cells, and plasma levels of many such miRNAs track blood cell counts or hemolysis rather than tumor-specific biology. The authors caution that blood cell effects can be larger than reported cancer-vs-control differences and recommend interpreting circulating miRNA biomarkers alongside complete blood counts.
Key findings
- Of 79 literature-reported solid tumor circulating miRNA biomarkers, 58% were highly expressed in one or more blood cell type; the abstract reports 47/79, while the Results section reports 46/79.
- Plasma levels of myeloid-expressed miRNAs (e.g., miR-223, miR-197, miR-574-3p, let-7a) and lymphoid-expressed miR-150 correlated with corresponding white blood cell counts, with >50-fold differences in plasma miRNA levels between patients with the highest and lowest overall cell counts.
- In hemolyzed specimens, all four RBC-associated miRNAs (miR-486-5p, miR-451, miR-92a, miR-16) increased 20–30 fold in plasma (p<0.0000001), whereas none of six non-RBC-associated miRNAs were significantly increased.
- In a patient undergoing myeloablative chemotherapy and autologous hematopoietic stem cell transplant, plasma miR-223 and miR-150 tracked closely with changes in myeloid and lymphoid blood counts, respectively.
Methods
- qRT-PCR profiling of 369 miRNAs was performed on FACS-sorted blood cell populations, plasma, and whole blood; 4 independent FACS experiments used peripheral blood from one healthy male donor.
- A cohort of 42 consecutive residual patient plasma specimens with complete differential blood counts was used to correlate ten selected miRNAs with blood cell counts; one additional transplant patient had serial plasma samples collected prospectively.
- Main analyses included correlation of plasma miRNA levels with blood cell counts, comparison of hemolyzed vs. non-hemolyzed specimens, and unsupervised hierarchical clustering of plasma miRNA expression across patient samples.
Limitations
- Stated: the study does not directly assess the relative contribution of different blood cell types to plasma miRNA or examine mechanisms of miRNA release into plasma.
- Stated: pre-analytical and analytical sources of variation, including collection, processing, RNA extraction, measurement, data acquisition, and normalization, may influence plasma miRNA levels.
- Evident: RBC-expressed miRNAs could not be correlated with RBC counts because of limited variation in RBC count/hematocrit in the cohort; only 3 of 42 plasma specimens were hemolyzed; the transplant time-course involved a single patient; and the text contains minor numerical discrepancies (e.g., 47/79 vs. 46/79; 21 specimens vs. 25 timepoints; 32- vs. 33-day period).
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Claims the paper makes
17 Own result · 10 Own interpretation · 6 Own method · 2 Partly supported · 1 Supported so far · 1 No full text of the sources · 1 No basis given · accuracy not yet measured
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“we observed variation attributable to blood cell effects that was greater in magnitude than many of the differences reported between cancer patients and controls (13, 15, 20).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
What the sources say
- Supportedcites [13] Boeri, 2011, MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer, Proc Natl Acad Sci U S A source
The Results report significant differences in plasma miRNA ratios between diagnostic and disease-free samples and describe a signature distinguishing lung cancer patients from disease-free controls. The blood-cell effects and the comparison of their magnitude are the citing authors’ own observation, not a finding attributed to this source. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites [15] Ng, 2009, Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening, Gut source
- Could not verifycites [20] Hu, 2010, Serum microRNA signatures identified in a genome-wide serum microRNA expression profiling predict survival of non-small-cell lung cancer, J Clin Oncol sourceExperimental — accuracy not yet measured
The Methods and Results describe serum miRNA measurements and survival comparisons among patients with non-small-cell lung cancer, not differences between cancer patients and controls. The Discussion mentions similarities between serum and blood-cell miRNA profiles in healthy people, but gives no magnitude of blood-cell effects to compare with cancer–control differences. Searched for cancer–control expression differences and blood-cell-effect magnitudes; our copy does not establish the attributed comparison. (LLM, conf=0.76)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: passes — The paper gives a reason why it holds.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“A recent study published in PNAS found that increased ratios of neutrophil-expressed plasma miRNAs (miR-197, miR-142-3p, miR-140-5p, miR-17, miR-21) compared to RBC-expressed miRNAs (miR-92a, miR-486-5p, miR-16, and miR-451) were associated with poorer outcomes in non-small cell lung cancer patients (13).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
What the sources say
- Partly supportedcites [13] Boeri, 2011, MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer, Proc Natl Acad Sci U S A sourceExperimental — accuracy not yet measured
The Results (page unavailable in our copy) associate plasma miRNA ratios with poor prognosis and report that miR-486-5p was down-regulated relative to several of the listed miRNAs in patients with bad outcomes. The paper does not identify the miRNAs as neutrophil- or RBC-expressed, or establish the claimed increase for all of the specified ratios. (LLM, conf=0.86)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Plasma levels of the myeloid-expressed miRNAs let-7a, miR-223, miR-197, and miR-574-3p showed significant positive correlations with myeloid blood cell counts (granulocytes and platelets) (Fig. 2B – left)”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plaincorrelationaln = 42- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“3 of the 42 plasma specimens were noted to be hemolyzed.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plainn = 42- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“all four RBC-associated miRNAs were increased by 20-30 fold in hemolyzed plasma”
- Also stated in: § Abstract · plain
“were significantly increased in hemolyzed specimens (20-30 fold plasma increase; p<0.0000001)”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plaindirectn = 42 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Hemolysis determined by visual inspection accurately identifies specimens with red blood cell lysis sufficient to release miRNAs.
- Also stated in: § Abstract · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“RBC-expressed miRNAs we had selected did not show correlations with white blood cell or platelet counts (Fig. 2B - left).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Comparing expression profiles of miRNAs detectable in plasma to miRNA profiles of blood cells demonstrated that the distribution of miRNA expression values in plasma mirrors that of blood cells (Fig. 1).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“plasma levels of a non-blood cell expressed miRNA (miR-122) did not strongly correlate with blood cell counts”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plainn = 42- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“plasma levels of the myeloid-enriched miRNA, miR-223, closely tracked with changes in myeloid blood counts (platelets and neutrophils)”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plaincorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most of the blood cell expressed biomarkers (42/46, 91%) were also present at considerable basal levels in healthy donor plasma (>50th percentile among all miRNAs detected)”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 8
- It may state two separate claims as one. 5
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“An additional 12 control arrays were performed on serial 2-fold dilutions of 30 μl of plasma from a single healthy donor to determine the analytic measurement ranges for each qPCR assay on the Exiqon array as previously described (7).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > qRT-PCR
What the sources say
- Partly supportedcites [7] Arroyo, 2011, Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma, Proc Natl Acad Sci U S A sourceExperimental — accuracy not yet measured
The Results (page unavailable) describe dilution analysis of miRNAs from plasma or serum from the same donor to determine assay-specific quantification and detection limits. Materials and Methods (page unavailable) identifies the Exiqon arrays. Our copy does not specify 12 control arrays, serial twofold dilutions, or a 30 μl plasma sample. (LLM, conf=0.87)
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“plasma levels of liver-restricted miR-122 that we selected as a negative control were not significantly correlated to blood cell counts or influenced by red blood cell hemolysis.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“plasma levels of RBC-expressed miRNAs were tightly inter-correlated even among non-hemolyzed specimens, but not substantially correlated to six non-RBC expressed miRNAs we examined (Figs. S2B and S2C).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
plaincorrelationaln = 42- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“At least 79 miRNAs have been reported as plasma or serum miRNA biomarkers of solid tumors (i.e., non-hematopoietic malignancies), including prostate, lung, breast, colon, ovarian, esophageal, melanoma, and gastric cancer (Table S1).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > INTRODUCTION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A total of 4 independent FACS experiments were performed on a Becton Dickinson ARIA cell sorter on separate days, using peripheral blood from the same healthy male volunteer donor (H1-1).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > Fluorescence activated cell sorting (FACS)
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All plasma processing was performed in the specimen processing area of a large clinical laboratory using the same standardized plasma processing procedure applied to clinical specimens.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > Clinical samples and plasma preparation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This study does not directly assess the relative contribution of different blood cell types to plasma miRNA, or examine mechanisms of miRNA release into plasma.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All plasma RNA preparations were made from 200μL in duplicate to control for variation in the RNA preparation step.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > RNA isolation
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“our studies in the setting of myeloablative chemotherapy and hematopoietic stem cell transplant engraftment provide the first direct, in vivo evidence that blood cell abundance can influence circulating miRNA levels.”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
plaindirectSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Changes in plasma miRNA levels in the single transplant patient are attributable to changes in blood cell counts rather than other effects of myeloablative chemotherapy or transplant.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“elevated neutrophil counts are associated with shortened progression-free and overall survival in several cancers including non-small cell lung cancer and breast cancer (21, 22).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [21] Azab, 2011, Usefulness of the neutrophil-to-lymphocyte ratio in predicting short- and long-term mortality in breast cancer patients, Ann Surg Oncol source
- Not checked — no full text of the sourcecites [22] Teramukai, 2009, Pretreatment neutrophil count as an independent prognostic factor in advanced non-small-cell lung cancer: an analysis of Japan Multinational Trial Organisation LC00–03, Eur J Cancer source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All plasma was processed fresh on the same day of blood draw (never frozen).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > RNA isolation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper relies on this without support.
Changes in plasma miRNA levels in the single transplant patient are attributable to changes in blood cell counts rather than other effects of myeloablative chemotherapy or transplant.
“we examined miR-223 (myeloid cell-expressed) and miR-150 (lymphoid cell-expressed) miRNAs in the plasma of a patient over a time-course of myeloablative chemotherapy and hematopoietic stem cell transplant engraftment (Table S3).”
“demonstrating that white blood cell counts can significantly influence plasma levels of blood cell-expressed miRNAs.”
The paper relies on this without support.
Blood cell miRNA expression profiles measured in purified sorted blood cells reflect the contribution of those cell types to circulating plasma miRNAs in vivo.
“We used qRT-PCR to examine expression of 79 miRNAs reported as circulating solid tumor biomarkers in purified sub-populations of blood cells and in matched healthy donor plasma (9-13) (Fig. S1).”
“suggesting that blood cells could be a major source for these plasma miRNAs”
The paper relies on this without support.
The 42 residual patient specimens are representative of a general patient population for assessing correlations between blood cell counts and plasma miRNA levels.
“The cohort consisted of consecutive residual patient plasma samples collected at a single academic medical center, including both inpatients and outpatients with a wide variety of underlying diseases (Table S2).”
The paper relies on this without support.
Hemolysis determined by visual inspection accurately identifies specimens with red blood cell lysis sufficient to release miRNAs.
“specimen characteristics (such as hemolysis determined by visual inspection)”
“3 of the 42 plasma specimens were noted to be hemolyzed.”
The paper relies on this without support.
The 79 literature-reported solid tumor biomarkers are a representative set of circulating miRNA cancer biomarkers.
“At least 79 miRNAs have been reported as plasma or serum miRNA biomarkers of solid tumors (i.e., non-hematopoietic malignancies), including prostate, lung, breast, colon, ovarian, esophageal, melanoma, and gastric cancer (Table S1).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, many such miRNAs also appear to be abundant in epithelia (Supplemental Data 1) [22]”
From Novel Approach to Fecal Occult Blood Testing by Assay of Erythrocyte-Specific microRNA Markers (2017) · cites this paper as [22]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Similar to a recent manuscript on cell-free RNA in plasma [40] and consistent with other miRNA-based studies [41–43], we observed that most plasma miRNAs were RBC derived, followed by platelets, mesenchymal cells, and immune cells.”
From A curated human cellular microRNAome based on 196 primary cell types (2022) · cites this paper as [43]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“For example, in addition to globin mRNAs, red blood cells also contain highly abundant miRNAs including miR-486-5p and miR-451a (4,5).”
From Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries (2020) · cites this paper as [5]
The cited source says what the claim attributes to it.
In the citing paper
“Moreover, the upregulation of miR-486-5p, miR-92a, miR-16, and miR-451a in plasma are associated with increased hemolysis”
From Red Blood Cells as Potential Repositories of MicroRNAs in the Circulatory System (2020) · cites this paper as Pritchard et al., 2012
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The 3′UTR also contains specific binding sites for microRNAs such as miR-16-5p and miR-92a, which can inhibit translation or promote mRNA degradation [5].”
From Importance of the 3′UTR region in globin synthesis: identification of two novel HBA1 mutations causing α-Thalassemia (2025) · cites this paper as [5]
Experimental — accuracy not yet measured
In the citing paper
“Erythroid-specific miR-451a and miR-486-5p are two of the most dominant microRNAs (miRNAs) in human peripheral blood.”
From Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries (2020) · cites this paper as [5]
In the citing paper
“Pritchard et al. (2012) were among the first to highlight the problem of contamination of miRNAs derived from blood cells in the plasma of patients with cancer because of hemolysis occurring at the time of blood withdrawal or processing, thereby raising concern regarding their possible use as cancer biomarkers.”
From Red Blood Cells as Potential Repositories of MicroRNAs in the Circulatory System (2020) · cites this paper as Pritchard et al., 2012
In the citing paper
“miRNAs are known to be involved in cancer”
From Red Blood Cells as Potential Repositories of MicroRNAs in the Circulatory System (2020) · cites this paper as Pritchard et al., 2012
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
“fifty-eight percent (47/79) are highly expressed in one or more blood cell type”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > Abstract
Reported 58 · recomputed 59.493671
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > MATERIALS AND METHODS > Clinical samples and plasma preparation
“One patient (Study Code R46) had a total of 21 residual plasma specimens collected prospectively over a period of 33 days during the course of myeloablative chemotherapy and autologous hematopoietic stem cell transplant (Table S3).”
§ Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies > RESULTS
“We collected serial plasma samples and corresponding blood count data at 25 timepoints over a 32-day period (Fig. 2C).”
Cited works that were retracted
Works this paper cites that were later retracted, from the retraction notices publishers deposit. Major when the notice came out before this paper was published.
A note, not an issue: for example, a cited work that was retracted only after this paper was published, which its authors could not have known.
In the paper
“Taylor, 2008, MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer, Gynecol Oncol, 110, 13, 10.1016/j.ygyno.2008.04.033”
Cited work 10.1016/j.ygyno.2008.04.033 · retracted 2023-07-20 · notice 10.1016/j.ygyno.2023.06.002 · this paper published 2012-03-01
Citations
Cites
1 retracted
RETRACTED: MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer
Taylor, D. D., & Gerçel-Taylor, Ç. (2008) · Gynecologic Oncology · doi:10.1016/j.ygyno.2008.04.033 · Cited by 2,333
RetractedCirculating microRNAs as stable blood-based markers for cancer detection
Mitchell, P. S., Parkin, R. K., Kroh, E. M., Fritz, B. R., Wyman, S. K., Pogosova-Agadjanyan, E. L., Peterson, A., Noteboom, J., O'Briant, K. C., Allen, A., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0804549105 · Cited by 7,969
Self-citationChen, X., Ba, Y., Ma, L., Cai, X., Yin, Y., Wang, K., Guo, J., Zhang, Y., Chen, J., Guo, X., et al. (2008) · Cell Research · doi:10.1038/cr.2008.282 · Cited by 4,560
Arroyo, J. D., Chevillet, J. R., Kroh, E. M., Ruf, I. K., Pritchard, C. C., Gibson, D. F., Mitchell, P. S., Bennett, C. F., Pogosova-Agadjanyan, E. L., Stirewalt, D. L., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019055108 · Cited by 3,294
Self-citationLawrie, C. H., Gal, S., Dunlop, H. M., Pushkaran, B., Liggins, A. P., Pulford, K. A. F., Banham, A. H., Pezzella, F., Boultwood, J., Wainscoat, J. S., et al. (2008) · British Journal of Haematology · doi:10.1111/j.1365-2141.2008.07077.x · Cited by 1,757
Jia, Q.-W., Chen, Z.-H., Ding, X.-Q., Liu, J.-Y., Ge, P.-C., An, F.-H., Li, L.-H., Wang, L.-S., Ma, W.-Z., Yang, Z.-J., et al. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000478071 · Cited by 1,694
Kroh, E. M., Parkin, R. K., Mitchell, P. S., & Tewari, M. (2010) · Methods · doi:10.1016/j.ymeth.2010.01.032 · Cited by 1,184
Self-citationNg, E. K. O., Chong, W. W. S., Jin, H., Lam, E. K. Y., Shin, V. Y., Yu, J., Poon, T. C. W., Ng, S. S. M., & Sung, J. J. Y. (2009) · Gut · doi:10.1136/gut.2008.167817 · Cited by 1,151
Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis
Kosaka, N., Iguchi, H., & Ochiya, T. (2010) · Cancer Science · doi:10.1111/j.1349-7006.2010.01650.x · Cited by 1,147
Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer
Huang, Z., Huang, D., Ni, S., Peng, Z., Sheng, W., & Du, X. (2009) · International Journal of Cancer · doi:10.1002/ijc.25007 · Cited by 975
Cited by
Sorted by citations
Items 101–200 of 878
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Li, Y., & Kowdley, K. V. (2012) · Analytical Biochemistry · doi:10.1016/j.ab.2012.09.007 · Cited by 134
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Jacob, N. K., Cooley, J. V., Yee, T. N., Jacob, J., Alder, H., Wickramasinghe, P., Maclean, K. H., & Chakravarti, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057603 · Cited by 134
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Grasedieck, S., Sorrentino, A., Langer, C., Buske, C., Döhner, H., Mertens, D., & Kuchenbauer, F. (2013) · Blood · doi:10.1182/blood-2013-01-480079 · Cited by 135
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Jones, K., Nourse, J. P., Keane, C., Bhatnagar, A., & Gandhi, M. K. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-1024 · Cited by 132
Changes in circulating microRNAs levels with exercise modality
Banzet, S., Chennaoui, M., Girard, O., Racinais, S., Drogou, C., Chalabi, H., & Koulmann, N. (2013) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00075.2013 · Cited by 129
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Zanutto, S., Pizzamiglio, S., Ghilotti, M., Bertan, C. M., Ravagnani, F., Perrone, F., Leo, E., Pilotti, S., Verderio, P., Gariboldi, M., et al. (2014) · British Journal of Cancer · doi:10.1038/bjc.2013.819 · Cited by 128
Aushev, V. N., Zborovskaya, I. B., Лактионов, К. К., Girard, N., Cros, M., Herceg, Z., & Krutovskikh, V. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0078649 · Cited by 128
Quantification of Plasma miRNAs by Digital PCR for Cancer Diagnosis
Ma, J., Li, N., Guarnera, M., & Jiang, F. (2013) · Biomarker Insights · doi:10.4137/bmi.s13154 · Cited by 131
Issues and Prospects of microRNA-Based Biomarkers in Blood and Other Body Fluids
Chevillet, J. R., Lee, I., Briggs, H., He, Y., & Wang, K. (2014) · Molecules · doi:10.3390/molecules19056080 · Cited by 129
Biogenesis and function of extracellular miRNAs
Zhao, C., Sun, X., & Li, L. (2019) · ExRNA · doi:10.1186/s41544-019-0039-4 · Cited by 133
Wang, X., Sundquist, J., Zöller, B., Memon, A. A., Palmér, K., Sundquist, K., & Bennet, L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086792 · Cited by 125
Plasma miRNAs in diagnosis and prognosis of pancreatic cancer: A miRNA expression analysis
Xin Min, Z. H. O. U., Lu, Z., Wang, T., Huang, Z., Zhu, W., & Miao, Y. (2018) · Gene · doi:10.1016/j.gene.2018.06.037 · Cited by 123
Caserta, S., Kern, F., Cohen, J., Drage, S. M., Newbury, S. F., & Llewelyn, M. (2016) · Scientific Reports · doi:10.1038/srep28006 · Cited by 124
Circulating microRNAs predict biochemical recurrence in prostate cancer patients
BioResource, O. B. O. T. A. P. C., Selth, L. A., Townley, S. L., Bert, A. G., Stricker, P. D., Sutherland, P. D., Horvath, L. G., Goodall, G. J., Butler, L. M., & Tilley, W. D. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.369 · Cited by 120
Absolute quantification of cell-free microRNAs in cancer patients
Ferracin, M., Lupini, L., Salamon, I., Saccenti, E., Zanzi, M. V., Rocchi, A., Ros, L. D., Zagatti, B., Musa, G., Bassi, C., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.3859 · Cited by 118
Fujiwara, T., Uotani, K., Yoshida, A., Morita, T., Nezu, Y., Kobayashi, E., Yoshida, A., Uehara, T., Omori, T., Sugiu, K., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.16498 · Cited by 118
The potential of circulating cell-free RNA as a cancer biomarker: challenges and opportunities
Zaporozhchenko, I. A., Ponomaryova, A. A., RYKOVA, E. Y., & Laktionov, P. P. (2018) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2018.1425143 · Cited by 123
A comprehensive joint analysis of the long and short RNA transcriptomes of human erythrocytes.
Doss, J. F., Corcoran, D. L., Jima, D. D., Telen, M. J., Dave, S. S., & Chi, J.-T. (2015) · BMC Genomics · doi:10.1186/s12864-015-2156-2 · Cited by 113
Ostenfeld, M. S., Jensen, S. G., Jeppesen, D. K., Christensen, L.-L., Thorsen, S. B., Stenvang, J., Hvam, M. L., Thomsen, A. R., Mouritzen, P., Rasmussen, M. H., et al. (2016) · Journal of Extracellular Vesicles · doi:10.3402/jev.v5.31488 · Cited by 119
Pastorino, U., Boeri, M., Sestini, S., Sabia, F., Milanese, G., Silva, M., Suatoni, P., Verri, C., Cantarutti, A., Sverzellati, N., et al. (2022) · Annals of Oncology · doi:10.1016/j.annonc.2022.01.008 · Cited by 117
XenomiRs and miRNA homeostasis in health and disease
Witwer, K. W. (2012) · RNA Biology · doi:10.4161/rna.21619 · Cited by 115
Hirajima, S., Komatsu, S., Ichikawa, D., Takeshita, H., Konishi, H., Shiozaki, A., Morimura, R., Tsujiura, M., Nagata, H., Kawaguchi, T., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.148 · Cited by 116
Sierżęga, M., Kaczor, M. P., Kołodziejczyk, P., Kulig, J., Sanak, M., & Richter, P. (2017) · British Journal of Cancer · doi:10.1038/bjc.2017.190 · Cited by 114
Dampening Enthusiasm for Circulating MicroRNA in Breast Cancer
Leidner, R. S., Li, L., & Thompson, C. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057841 · Cited by 113
McDermott, A. M., Kerin, M. J., & Miller, N. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083718 · Cited by 113
Secretory microRNAs as biomarkers of cancer
Kai, K., Dittmar, R. L., & Sen, S. (2017) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2017.12.011 · Cited by 118
Different miRNA expression profiles between human breast cancer tumors and serum
Zhu, J., Zheng, Z., Wang, J., Sun, J., Wang, P., Cheng, X., Fu, L., Zhang, L., Wang, Z., & Li, Z. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00149 · Cited by 111
MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma
Patnaik, S. K., Yendamuri, S., Kannisto, E. D., Kucharczuk, J. C., Singhal, S. K., & Vachani, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046045 · Cited by 112
Extracellular MicroRNAs in Urologic Malignancies: Chances and Challenges
Huang, X., Liang, M., Dittmar, R. L., & Wang, L. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms140714785 · Cited by 110
Komatsu, S., Ichikawa, D., Hirajima, S., Kawaguchi, T., Miyamae, M., Okajima, W., Ohashi, T., Arita, T., Konishi, H., Shiozaki, A., et al. (2014) · British Journal of Cancer · doi:10.1038/bjc.2014.451 · Cited by 112
MicroRNAs in skeletal muscle and their regulation with exercise, ageing, and disease
Zacharewicz, E., Lamon, S., & Russell, A. P. (2013) · Frontiers in Physiology · doi:10.3389/fphys.2013.00266 · Cited by 115
The Potential Role of miR-451 in Cancer Diagnosis, Prognosis, and Therapy
Pan, X., Wang, R., & Wang, Z.-X. (2013) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-12-0802 · Cited by 108
miRNAs as novel biomarkers in the management of prostate cancer
Filella, X., & Foj, L. (2016) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2015-1073 · Cited by 110
Li, H., Liu, J., Chen, J., Wang, H., Yang, L., Chen, F., Fan, S., Wang, J., Shao, B., Yin, D., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03537-w · Cited by 107
Chang, P.-Y., Chen, C., Chang, Y., Tsai, W., You, J., Lin, G.-P., Chen, T.-W., Chen, J.-S., & Chan, E. (2016) · Oncotarget · doi:10.18632/oncotarget.7119 · Cited by 106
Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers
Khavari, B., & Cairns, M. J. (2020) · Cells · doi:10.3390/cells9081837 · Cited by 115
Circulating MicroRNAs as Biomarkers for Inflammatory Diseases
Mi, S., Zhang, J., Zhang, W., & Huang, R. S. (2013) · MicroRNA · doi:10.2174/2211536611302010007 · Cited by 108
Jin, C., Shi, W., Wang, F., Shen, X., Qi, J., Cong, H., Yuan, J., Shi, L., Zhu, B., Luo, X., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.10107 · Cited by 105
Detection of Circulating Parasite-Derived MicroRNAs in Filarial Infections
Tritten, L., Burkman, E. J., Moorhead, A. R., Satti, M., Geary, J. F., Mackenzie, C. D., & Geary, T. G. (2014) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0002971 · Cited by 108
Circulating miRNAs as New Blood-Based Biomarkers for Solid Cancers
Rédová, M., Šáňa, J., & Slabý, O. (2013) · Future Oncology · doi:10.2217/fon.12.192 · Cited by 103
Plasma miR‐122 and miR‐200 family are prognostic markers in colorectal cancer
Maierthaler, M., Benner, A., Hoffmeister, M., Surowy, H., Jansen, L., Knebel, P., Chang-Claude, J. C., Brenner, H., & Burwinkel, B. (2016) · International Journal of Cancer · doi:10.1002/ijc.30433 · Cited by 106
Distinctive Serum miRNA Profile in Mouse Models of Striated Muscular Pathologies
Vignier, N., Amor, F., Fogel, P., Duvallet, A., Poupiot, J., Charrier, S., Arock, M., Montus, M., Nelson, I. P., Richard, I., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055281 · Cited by 102
Unfolding the pathogenesis of scleroderma through genomics and epigenomics
Tsou, P., & Sawalha, A. H. (2017) · Journal of Autoimmunity · doi:10.1016/j.jaut.2017.05.004 · Cited by 103
MicroRNA-223 and miR-143 are important systemic biomarkers for disease activity in psoriasis
Løvendorf, M. B., Zibert, J. R., Gyldenløve, M., Røpke, M. A., & Skov, L. (2014) · Journal of Dermatological Science · doi:10.1016/j.jdermsci.2014.05.005 · Cited by 102
Pre-profiling factors influencing serum microRNA levels
MacLellan, S. A., MacAulay, C. E., Lam, S. C., & Garnis, C. (2014) · BMC Clinical Pathology · doi:10.1186/1472-6890-14-27 · Cited by 99
Circulating miRNA signatures of early pregnancy in cattle
Ioannidis, J., & Donadeu, F. X. (2016) · BMC Genomics · doi:10.1186/s12864-016-2529-1 · Cited by 99
Impact of long-term storage and freeze-thawing on eight circulating microRNAs in plasma samples
Matías‐García, P. R., Wilson, R., Mussack, V., Reischl, E., Waldenberger, M., Gieger, C., Anton, G., Peters, A., & Kühn-Steven, A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0227648 · Cited by 99
Mai, D., Zheng, Y., Guo, H., Ding, P., Bai, R., Li, M., Ye, Y., Zhang, J., Huang, X., Liu, D., et al. (2020) · Theranostics · doi:10.7150/thno.46241 · Cited by 101
Roles of micro RNA s in psoriasis: Immunological functions and potential biomarkers
Liu, Q., Wu, D., Han, L., Deng, J., Zhou, L., He, R., Lu, C., & Mi, Q. (2017) · Experimental Dermatology · doi:10.1111/exd.13249 · Cited by 98
Miyamae, M., Komatsu, S., Ichikawa, D., Kawaguchi, T., Hirajima, S., Okajima, W., Ohashi, T., Imamura, T., Konishi, H., Shiozaki, A., et al. (2015) · British Journal of Cancer · doi:10.1038/bjc.2015.366 · Cited by 101
Tsujiura, M., Komatsu, S., Ichikawa, D., Shiozaki, A., Konishi, H., Takeshita, H., Moriumura, R., Nagata, H., Kawaguchi, T., Hirajima, S., et al. (2014) · Gastric Cancer · doi:10.1007/s10120-014-0363-1 · Cited by 96
Guzman, N., Agarwal, K., Asthagiri, D. N., Yu, L., Saji, M., Ringel, M. D., & Paulaitis, M. E. (2015) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-14-0533 · Cited by 96
Pre-analytical variables in miRNA analysis
Becker, N., & Lockwood, C. M. (2013) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2013.02.015 · Cited by 95
Ma, Y., Vilanova, D., Atalar, K., Delfour, O., Edgeworth, J., Ostermann, M., Hernández-Fuentes, M. P., Razafimahatratra, S., Michot, B., Persing, D. H., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075918 · Cited by 94
From laboratory to clinic: Translation of extracellular vesicle based cancer biomarkers
Yekula, A., Muralidharan, K., Kang, K. M., Wang, L., Balaj, L., & Carter, B. S. (2020) · Methods · doi:10.1016/j.ymeth.2020.02.003 · Cited by 94
Isothermally Sensitive Detection of Serum Circulating miRNAs for Lung Cancer Diagnosis
Li, Y., Liang, L., & Zhang, C. (2013) · Analytical Chemistry · doi:10.1021/ac403462f · Cited by 94
The biology of circulating micro RNA s in cardiovascular disease
Min, P., & Chan, S. Y. (2015) · European Journal of Clinical Investigation · doi:10.1111/eci.12475 · Cited by 98
Cookson, V. J., Bentley, M. A., Hogan, B. V., Horgan, K. J., Hayward, B. E., Hazelwood, L. D., & Hughes, T. A. (2012) · Cellular Oncology · doi:10.1007/s13402-012-0089-1 · Cited by 91
Urinary Markers in Bladder Cancer: An Update
Santoni, G., Morelli, M. B., Amantini, C., & Battelli, N. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00362 · Cited by 91
Urinary Exosomal MicroRNAs as Potential Non-invasive Biomarkers in Breast Cancer Detection
Hirschfeld, M., Rücker, G., Weiß, D., Berner, K., Ritter, A., Jäger, M., & Erbes, T. (2020) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-020-00453-y · Cited by 91
Anfossi, S., Giordano, A., Gao, H., Cohen, E. N., Tin, S., Wu, Q., Garza, R. J., Debeb, B. G., Álvarez, R. H., Valero, V., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0083113 · Cited by 95
Teruel‐Montoya, R., Kong, X., Abraham, S., Ma, L., Kunapuli, S. P., Holinstat, M. A., Shaw, C. A., McKenzie, S. E., Edelstein, L. C., & Bray, P. F. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102259 · Cited by 93
Harling, L., Lambert, J., Ashrafian, H., Darzi, A. W., Gooderham, N. J., & Athanasiou, T. (2016) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezw245 · Cited by 90
Circulating miR-18a: a sensitive cancer screening biomarker in human cancer.
Komatsu, S., Ichikawa, D., Takeshita, H., Morimura, R., Hirajima, S., Tsujiura, M., Kawaguchi, T., Miyamae, M., Nagata, H., Konishi, H., et al. (2014) · PubMed · Cited by 90
Circulating miRNAs miR-34a and miR-150 associated with colorectal cancer progression
Aherne, S. T., Madden, S. F., Hughes, D. J., Pardini, B., Naccarati, A., Levý, M., Vodička, P., Neary, P. C., Dowling, P., & CLYNES, M. M. (2015) · BMC Cancer · doi:10.1186/s12885-015-1327-5 · Cited by 89
Examining plasma microRNA markers for colorectal cancer at different stages
Sun, Y., Liu, Y., Cogdell, D. E., Călin, G. A., Sun, B., Kopetz, S., Hamilton, S. R., & Zhang, W. (2016) · Oncotarget · doi:10.18632/oncotarget.7196 · Cited by 89
Measurements Methods for the Development of MicroRNA-Based Tests for Cancer Diagnosis
Precazzini, F., Detassis, S., Imperatori, A. S., Denti, M. A., & Campomenosi, P. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22031176 · Cited by 91
microRNAs Make the Call in Cancer Personalized Medicine
Detassis, S., Grasso, M., Vescovo, V. D., & Denti, M. A. (2017) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2017.00086 · Cited by 88
Poel, D., Buffart, T. E., Oosterling-Jansen, J. E. W., Verheul, H. M. W., & Voortman, J. (2018) · Experimental & Molecular Medicine · doi:10.1038/emm.2017.288 · Cited by 88
Sartorius, K., Makarova, J. A., Sartorius, B. K. D., An, P., Winkler, C. A., Chuturgoon, A. A., & Kramvis, A. (2019) · Cells · doi:10.3390/cells8121504 · Cited by 88
Iftikhar, H., & Carney, G. E. (2016) · BioEssays · doi:10.1002/bies.201500130 · Cited by 87
Serum overexpression of miR-301a and miR-23a in patients with colorectal cancer
Karimi, N., Feizi, M. A. H., Safaralizadeh, R., Hashemzadeh, S., Baradaran, B., Shokouhi, B., & Teimourian, S. (2019) · Journal of the Chinese Medical Association · doi:10.1097/jcma.0000000000000031 · Cited by 87
Fernández‐Mercado, M., Manterola, L., Larrea, E., Goicoechea, I., Arestin, M., Armesto, M., Otaegui, D., & Lawrie, C. H. (2015) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.12625 · Cited by 89
Leger, K. J., Leonard, D., Nielson, D., de Lemos, J. A., Mammen, P. P. A., & Winick, N. J. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.116.004653 · Cited by 87
Margue, C., Reinsbach, S. E., Philippidou, D., Beaume, N., Walters, C., Schneider, J. G., Nashan, D., Behrmann, I., & Kreis, S. (2015) · Oncotarget · doi:10.18632/oncotarget.3661 · Cited by 87
The role of epigenetic changes in preeclampsia
Kamrani, A., Alipourfard, I., Ahmadi‐Khiavi, H., Yousefi, M., Rostamzadeh, D., Izadi, M., & Ahmadi, M. (2019) · BioFactors · doi:10.1002/biof.1542 · Cited by 87
Circulating serum miR-223-3p and miR-16-5p as possible biomarkers of early rheumatoid arthritis
Dunaeva, M., Blom, J., Thurlings, R. M., & Pruijn, G. J. M. (2018) · Clinical & Experimental Immunology · doi:10.1111/cei.13156 · Cited by 86
MicroRNAs in colorectal cancer: Small molecules with big functions
Yu, X., Yang, H., Zhao, L., Lau, W. B., Lau, B., Ren, N., Hu, Y., Yi, T., Zhao, X., Zhou, S., et al. (2014) · Cancer Letters · doi:10.1016/j.canlet.2014.11.051 · Cited by 84
High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer
Leidinger, P., Brefort, T., Backes, C., Krapp, M., Galata, V., Beier, M., Kohlhaas, J., Huwer, H., Meese, E. U., & Keller, A. (2015) · Oncotarget · doi:10.18632/oncotarget.6566 · Cited by 84
Huo, D., Clayton, W., Yoshimatsu, T. F., Chen, J., & Olopade, O. I. (2016) · Oncotarget · doi:10.18632/oncotarget.10485 · Cited by 85
Wang, C., Ding, M., Xia, M., Chen, S., Le, A. V., Soto‐Gil, R. W., Shen, Y., Wang, N., Wang, J., Gu, W., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.07.034 · Cited by 84
Regulation of mi RNA biogenesis and turnover in the immune system
Bronevetsky, Y., & Ansel, K. M. (2013) · Immunological Reviews · doi:10.1111/imr.12059 · Cited by 84
Vigneron, N., Meryet‐Figuière, M., Guttin, A., Issartel, J., Lambert, B., Briand, M., Louis, M.-H., Vernon, M., Lebailly, P., Lécluse, Y., et al. (2016) · Molecular Oncology · doi:10.1016/j.molonc.2016.03.005 · Cited by 84
Smith-Vikos, T., Liu, Z., Parsons, C., Gorospe, M., Ferrucci, L., Gill, T. M., & Slack, F. J. (2016) · Aging · doi:10.18632/aging.101106 · Cited by 86
Red Blood Cells as Potential Repositories of MicroRNAs in the Circulatory System
Sun, L., Yu, Y., Niu, B., & Wang, D. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00442 · Cited by 83
Biomarkers and Lung Cancer Early Detection: State of the Art
Dama, E., Colangelo, T., Fina, E., Cremonesi, M., Kallikourdis, M., Veronesi, G., & Bianchi, F. (2021) · Cancers · doi:10.3390/cancers13153919 · Cited by 84
Identification of cardiac-related circulating microRNA profile in human chronic heart failure
Li, H., Fan, J., Yin, Z., Wang, F., Chen, C., & Wang, D. W. (2015) · Oncotarget · doi:10.18632/oncotarget.6631 · Cited by 83
The origin, function, and diagnostic potential of extracellular microRNAs in human body fluids
Liang, H., Gong, F., Zhang, S., Zhang, C., Zen, K., & Chen, X. (2013) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1208 · Cited by 84
Circulating microRNAs in cancer: Hope or hype?
Singh, R., Ramasubramanian, B., Kanji, S., Chakraborty, A., Haque, S. J., & Chakravarti, A. (2016) · Cancer Letters · doi:10.1016/j.canlet.2016.07.002 · Cited by 82
Khan, J., Lieberman, J. A., & Lockwood, C. M. (2017) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2016-0471 · Cited by 82
Opportunities for microRNAs in the crowded field of cardiovascular biomarkers
Halushka, P. V., Goodwin, A. J., & Halushka, M. K. (2019) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-012827 · Cited by 84
Bijkerk, R., Duijs, J. M. G. J., Khairoun, M., ter Horst, C. J. H., van der Pol, P., Mallat, M. J. K., Rotmans, J. I., de Vries, A. P. J., de Koning, E. J. P., de Fijter, J. W., et al. (2015) · American Journal of Transplantation · doi:10.1111/ajt.13072 · Cited by 82
A novel serum microRNA panel to discriminate benign from malignant ovarian disease
Langhe, R., Norris, L., Saadeh, F. A., Blackshields, G., Varley, R., Harrison, A., Gleeson, N., Spillane, C. D., Martin, C. M., O’Donnell, D. M., et al. (2014) · Cancer Letters · doi:10.1016/j.canlet.2014.10.010 · Cited by 82
Circulating miR-148b and miR-133a as biomarkers for breast cancer detection
Shen, J., Hu, Q., Schrauder, M. G., Yan, L., Wang, D., Medico, L., Guo, Y., Yao, S., Zhu, Q., Liu, B., et al. (2014) · Oncotarget · doi:10.18632/oncotarget.2014 · Cited by 82
Circulating microRNAs: potential biomarkers for common malignancies
Khoury, S., & Tran, N. (2015) · Biomarkers in Medicine · doi:10.2217/bmm.14.102 · Cited by 81
Extracellular microRNAs as Biomarkers in Human Disease
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Metadata
- Authors
- Pritchard, C. C., Kroh, E., Wood, B., Arroyo, J. D., Dougherty, K. J., Miyaji, M. M., Tait, J. F., & Tewari, M.
- Affiliations
- University of Washington (US)
- Corresponding author
- Tewari, Muneesh
- Venue
- Cancer Prevention Research
- Published
- 2012-03-01
- Volume
- 5
- Issue
- 3
- Pages
- 492-497
- ISSN
- 1940-6207 (ISSN-L)
- 1940-6215
- PMC
- PMC4186243
- OpenAlex
- W2140775205
- Cited by
- 879
- References
- 34
- Citations by year
- 2026: 29 · 2025: 28 · 2024: 36 · 2023: 25 · 2022: 45 · 2021: 61 · 2020: 59 · 2019: 56 · 2018: 71 · 2017: 86 · 2016: 87 · 2015: 103 · 2014: 95 · 2013: 71 · 2012: 27
- FWCI
- 20.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Prevention Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5p50ca083636-15)
- National Cancer Institute (P50-CA083636, P30CA015704, P50CA097186)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK085714)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- circulating microRNAs, cell-free microRNAs, tumor markers, hemolysis, white blood cell count, red blood cell count, myeloid cells, lymphoid cells, hematopoietic stem cell transplantation, miR-223, miR-150, miR-574-3p, miR-197, miR-451, miR-486-5p, miR-92a, miR-16
- MeSH terms
- Erythrocytes, Humans, Neoplasms, Plasma, RNA, Messenger, Biomarkers, Tumor, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, MicroRNAs, Real-Time Polymerase Chain Reaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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