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 1,755
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 301–400 of 878
Vanhaverbeke, M., Attard, R., Barteková, M., Ben‐Aicha, S., Brandenburger, T., de Gonzalo‐Calvo, D., Emanueli, C., Farrugia, R. C., Grillari, J., Hackl, M., et al. (2021) · Cardiovascular Research · doi:10.1093/cvr/cvab327 · Cited by 54
Challenges and future scope of exosomes in the treatment of cardiovascular diseases
Ranjan, P., Colin, K., Dutta, R. K., & Verma, S. K. (2022) · The Journal of Physiology · doi:10.1113/jp282053 · Cited by 55
Circulating miRNA in patients with non-alcoholic fatty liver disease and coronary artery disease
Mehta, R., Otgonsuren, M., Younoszai, Z., Allawi, H., Raybuck, B. D., & Younossi, Z. M. (2016) · BMJ Open Gastroenterology · doi:10.1136/bmjgast-2016-000096 · Cited by 54
Caserta, S., Mengozzi, M., Kern, F., Newbury, S. F., Ghezzi, P., & Llewelyn, M. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01977 · Cited by 56
Kloten, V., Neumann, M. H., Pasquale, F. D., Sprenger‐Haussels, M., Shaffer, J. M., Schlumpberger, M., Herdean, A., Betsou, F., Ammerlaan, W., af Hällström, T., et al. (2019) · Clinical Chemistry · doi:10.1373/clinchem.2019.303271 · Cited by 54
Wang, M., Zhang, H., Yang, F., Qiu, R., Zhao, X., Gong, Z., Yu, W., Zhou, B., Shen, B., & Zhu, W. (2019) · Journal of Cellular Physiology · doi:10.1002/jcp.29367 · Cited by 53
El‐Daly, S. M., Gouhar, S. A., & Elmageed, Z. Y. A. (2022) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.121.000896 · Cited by 53
Permuth‐Wey, J., Chen, D., Fulp, W. J., Yoder, S., Zhang, Y., Georgeades, C., Husain, K. M., Centeno, B. A., Magliocco, A. M., Coppola, D., et al. (2015) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-15-0094 · Cited by 53
Regulation of miRNAs by herbal medicine: An emerging field in cancer therapies
Mohammadi, A., Mansoori, B., & Baradaran, B. (2016) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2016.12.023 · Cited by 54
Panizo, S., Carrillo‐López, N., Naves‐Díaz, M., Solache-Berrocal, G., Martínez‐Arias, L., Rodrigues-Díez, R. R., Fernández-Vázquez, A., Martínez‐Salgado, C., Ruiz‐Ortega, M., Dusso, A., et al. (2017) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfx060 · Cited by 53
Santangelo, L., Bordoni, V., Montaldo, C., Cimini, E., Zingoni, A., Battistelli, C., D’Offizi, G., Capobianchi, M. R., Santoni, A., Tripodi, M., et al. (2018) · Liver International · doi:10.1111/liv.13700 · Cited by 53
Circulating microRNA biomarkers for lung cancer detection in Western populations
Yu, H., Guan, Z., Ćuk, K., Brenner, H., & Zhang, Y. (2018) · Cancer Medicine · doi:10.1002/cam4.1782 · Cited by 53
Circulating microRNA profile throughout the menstrual cycle
Rekker, K., Saare, M., Roost, A. M., Salumets, A., & Peters, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081166 · Cited by 52
Circulating RNA Molecules as Biomarkers in Liver Disease
Enache, L. S., Enache, E. L., Ramière, C., Diaz, O., Bancu, L. A., Sin, A. I., & André, P. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms151017644 · Cited by 52
Serum miR-21, miR-26a and miR-101 as potential biomarkers of hepatocellular carcinoma
Zhuang, C., Jiang, W., Huang, D., Xu, L., Yang, Q., Zheng, L., Wang, X., & Hu, L. (2015) · Clinics and Research in Hepatology and Gastroenterology · doi:10.1016/j.clinre.2015.11.002 · Cited by 52
van Vliet, E. A., Puhakka, N., Mills, J. D., Srivastava, P. K., Johnson, M. R., Roncon, P., Gupta, S. D., Karttunen, J., Simonato, M., Łukasiuk, K., et al. (2017) · Epilepsia · doi:10.1111/epi.13915 · Cited by 52
Lassen, T. R., Just, J., Hjortbak, M. V., Jespersen, N. R., Stenz, K. T., Gu, T., Yan, Y., Su, J., Hansen, J., Bæk, R., et al. (2021) · Basic Research in Cardiology · doi:10.1007/s00395-021-00856-w · Cited by 54
Thinking small: towards microRNA-based therapeutics for anxiety disorders
Scott, K. A., Hoban, A. E., Clarke, G., Moloney, G. M., Dinan, T. G., & Cryan, J. F. (2015) · Expert Opinion on Investigational Drugs · doi:10.1517/13543784.2014.997873 · Cited by 52
Yamada, A., Cox, M. A., Gaffney, K., Moreland, A., Boland, C. R., & Goel, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112481 · Cited by 51
Wang, L., Liu, Y., Du, L., Li, J., Jiang, X., Zheng, G., Qu, A., Wang, H., Wang, L., Zhang, X., et al. (2012) · Molecular Medicine Reports · doi:10.3892/mmr.2015.3428 · Cited by 51
Steen, S. O., Iversen, L. V., Carlsen, A. L., Burton, M., Nielsen, C. T., Jacobsen, S., & Heegaard, N. H. H. (2014) · The Journal of Rheumatology · doi:10.3899/jrheum.140502 · Cited by 51
Vesicle Trafficking and RNA Transfer Add Complexity and Connectivity to Cell–Cell Communication
Roberts, C. T., & Kurre, P. (2013) · Cancer Research · doi:10.1158/0008-5472.can-13-0265 · Cited by 51
Circulating microRNA Profiles during the Bovine Oestrous Cycle
Ioannidis, J., & Donadeu, F. X. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158160 · Cited by 51
Zhao, K., Liang, G., Sun, X., & Guan, L. L. (2016) · BMC Genomics · doi:10.1186/s12864-016-2962-1 · Cited by 51
Komabayashi, Y., Kishibe, K., Nagato, T., Ueda, S., Takahara, M., & Harabuchi, Y. (2016) · Hematological Oncology · doi:10.1002/hon.2360 · Cited by 51
Yuan, Z., Baker, K. K., Redman, M. W., Wang, L., Adams, S. V., Yu, M., Dickinson, B., Makar, K. W., Ulrich, N., Böhm, J., et al. (2017) · British Journal of Cancer · doi:10.1038/bjc.2017.266 · Cited by 51
Fu, Y., Wang, N., Yang, A., Xu, Z., Zhang, W., Liu, H., Law, H., & Yan, F. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c03441 · Cited by 51
Barteneva, N. S., Baiken, Y., Fasler‐Kan, E., Alibek, K., Wang, S., Maltsev, N., Ponomarev, E. D., Sautbayeva, Z., Kauanova, S., Moore, A. V., et al. (2017) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2017.06.005 · Cited by 50
Stirm, L., Huypens, P., Sass, S., Batra, R., Fritsche, L., Brucker, S. Y., Abele, H., Hennige, A. M., Theis, F. J., Beckers, J., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-19200-9 · Cited by 49
Vasudeva, K., & Munshi, A. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14695 · Cited by 49
Isolation of Cell-Free miRNA from Biological Fluids: Influencing Factors and Methods
Bryzgunova, O. E., Konoshenko, M. Y., Zaporozhchenko, I. A., Yakovlev, A., & Laktionov, P. P. (2021) · Diagnostics · doi:10.3390/diagnostics11050865 · Cited by 49
Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review
Ali, H., Harting, R., de Vries, R., Ali, M., Würdinger, T., & Best, M. G. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.665235 · Cited by 49
Han, Q., Zhang, D., Zhang, R., Tang, J., Xu, K., Shao, M., Li, Y., Du, P., Zhang, R., Yang, D., et al. (2022) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2022.131676 · Cited by 48
Non-Coding RNAs in Primary Liver Cancer
Ghidini, M., & Braconi, C. (2015) · Frontiers in Medicine · doi:10.3389/fmed.2015.00036 · Cited by 48
Plasma miR-19b and miR-183 as Potential Biomarkers of Lung Cancer
Zaporozhchenko, I. A., Morozkin, E. S., Skvortsova, T. E., Ponomaryova, A. A., RYKOVA, E. Y., Чердынцева, Н. В., Polovnikov, E. S., Pashkovskaya, O. A., Pokushalov, E. A., Vlassov, V. V., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0165261 · Cited by 48
Pan, C., Yan, X., Li, H., Huang, L., Yin, M., Yang, Y. P., Gao, R., Hong, L., Ma, Y., Shi, C., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.19344 · Cited by 48
MicroRNA profiling reveals distinct profiles for tissue-derived and cultured endothelial cells
Kuosmanen, S. M., Kansanen, E., Sihvola, V., & Levonen, A.-L. (2017) · Scientific Reports · doi:10.1038/s41598-017-11487-4 · Cited by 48
Cacheux, J., Bancaud, A., Leïchlé, T., & Cordelier, P. (2019) · Frontiers in Chemistry · doi:10.3389/fchem.2019.00815 · Cited by 48
MicroRNAs in mesothelioma: from tumour suppressors and biomarkers to therapeutic targets.
Reid, G. (2015) · Europe PMC (PubMed Central) · doi:10.3978/j.issn.2072-1439.2015.04.56 · Cited by 47
Gardiner, A. S., Gutierrez, H. L., Luo, L., Davies, S., Savage, D. D., Bakhireva, L. N., & Perrone‐Bizzozero, N. I. (2016) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.13026 · Cited by 47
Krauskopf, J., de Kok, T. M. C. M., Schomaker, S., Gosink, M. M., Burt, D. A., Chandler, P. A., Warner, R. L., Johnson, K. J., Caiment, F., Kleinjans, J. C. S., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177928 · Cited by 47
Hirai, T., Ikeda, K., Tsushima, H., Fujishiro, M., Hayakawa, K., Yoshida, Y., Morimoto, S., Yamaji, K., Takasaki, Y., Takamori, K., et al. (2018) · Inflammation and Regeneration · doi:10.1186/s41232-017-0058-1 · Cited by 47
Down-regulation of traditional oncomiRs in plasma of breast cancer patients
Jurkovičová, D., Smolková, B., MAGYERKOVA, M., Šestáková, Z., Kajabová, V. H., KULCSAR, L., Zmetakova, I., Kalinkova, L., Krivulcik, T., Karaba, M., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.20484 · Cited by 47
Sharapova, T., Devanarayan, V., LeRoy, B. E., Liguori, M. J., Blomme, E. A. G., Buck, W. R., & Maher, J. M. (2015) · Veterinary Pathology · doi:10.1177/0300985815591076 · Cited by 46
Ormseth, M. J., Solus, J. F., Sheng, Q., Ye, F., Wu, Q., Guo, Y. P., Oeser, A. M., Allen, R. M., Vickers, K. C., & Stein, C. (2019) · The Journal of Rheumatology · doi:10.3899/jrheum.181029 · Cited by 46
Extracellular miRNAs as Biomarkers of Head and Neck Cancer Progression and Metastasis
Nowicka, Z., Stawiski, K., Tomasik, B., & Fendler, W. M. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20194799 · Cited by 46
Serum MicroRNA Signature as a Diagnostic and Therapeutic Marker in Patients with Psoriatic Arthritis
Wade, S. M., McGarry, T., Wade, S. C., Fearon, U., & Veale, D. J. (2020) · The Journal of Rheumatology · doi:10.3899/jrheum.190602 · Cited by 46
The Role of Long Non-Coding RNAs in Thyroid Cancer
Peng, X., Zhang, K., Ma, L., Xu, J., & Chang, W. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00941 · Cited by 45
Ferrajoli, A., Ivan, C., Ciccone, M., Shimizu, M., Kita, Y., Ohtsuka, M., D’Abundo, L., Qiang, J., Lerner, S. A., Nouraee, N., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.04.018 · Cited by 45
Pacholewska, A., Kraft, M., Gerber, V., & Jagannathan, V. (2017) · Genes · doi:10.3390/genes8120383 · Cited by 45
MicroRNAs in Lupus Nephritis–Role in Disease Pathogenesis and Clinical Applications
So, B. Y. F., Yap, D. Y. H., & Chan, T. M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms221910737 · Cited by 46
Circulating miRNAs as biomarkers for endocrine disorders
Butz, H., Németh, K., Rácz, K., & Patócs, A. (2015) · Journal of Endocrinological Investigation · doi:10.1007/s40618-015-0316-5 · Cited by 45
Emerging roles of circular RNAs in liver cancer
Louis, C., Leclerc, D., & Coulouarn, C. (2021) · JHEP Reports · doi:10.1016/j.jhepr.2021.100413 · Cited by 46
miRNA as a Biomarker for the Early Detection of Colorectal Cancer
Coleman, D., & Kuwada, S. K. (2024) · Genes · doi:10.3390/genes15030338 · Cited by 43
Rounge, T. B., Lauritzen, M., Langseth, H., Enerly, E., Lyle, R., & Gislefoss, R. E. (2015) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-15-0289 · Cited by 43
Ramón, L., Martos, L., Fernández‐Pardo, Á., Oto, J., Medina, P., España, F., & Navarro, S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187005 · Cited by 43
Zhang, Y., Roth, J. A., Yu, H., Ye, Y., Xie, K., Zhao, H., Chang, D. W., Huang, M., Li, H., Qu, J., et al. (2018) · Carcinogenesis · doi:10.1093/carcin/bgy132 · Cited by 43
A comparative characterization of the circulating miRNome in whole blood and serum of HCC patients
Pascut, D., Krmac, H., Gilardi, F., Patti, R., Calligaris, R., Crocè, L. S., & Tiribelli, C. (2019) · Scientific Reports · doi:10.1038/s41598-019-44580-x · Cited by 43
The Role of MicroRNA as Clinical Biomarkers for Breast Cancer Surgery and Treatment
Davey, M. G., Davies, M., Lowery, A., Miller, N., & Kerin, M. J. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22158290 · Cited by 43
Exercise, Skeletal Muscle and Circulating microRNAs
Russell, A. P., & Lamon, S. (2015) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2015.07.018 · Cited by 43
Methylated DNA and microRNA in Body Fluids as Biomarkers for Cancer Detection
Ma, Y., Wang, X., & Jin, H. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms140510307 · Cited by 42
Huang, C.-H., Wei, J. C., Chang, W., CHIOU, S.-Y., Chou, C.-H., Lin, Y.-J., Hung, P., & Wong, R. (2014) · The Journal of Rheumatology · doi:10.3899/jrheum.130515 · Cited by 42
Circulating MicroRNA Biomarkers for Lung Cancer Detection in East Asian Populations
Yu, H., Guan, Z., Ćuk, K., Zhang, Y., & Brenner, H. (2019) · Cancers · doi:10.3390/cancers11030415 · Cited by 42
Serum microRNA-based prediction of responsiveness to eribulin in metastatic breast cancer
Satomi, N., Shimomura, A., Matsuzaki, J., Yamamoto, Y., Kawauchi, J., Takizawa, S., Aoki, Y., Sakamoto, H., Kato, K., Shimizu, C., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0222024 · Cited by 42
The Role of microRNA in Pancreatic Cancer
Smolarz, B., Durczyński, A., Romanowicz, H., & Hogendorf, P. (2021) · Biomedicines · doi:10.3390/biomedicines9101322 · Cited by 42
Grieco, G. E., Besharat, Z. M., Licata, G., Fignani, D., Brusco, N., Nigi, L., Formichi, C., Pò, A., Sabato, C., Dardano, A., et al. (2022) · Translational research · doi:10.1016/j.trsl.2022.03.008 · Cited by 43
microRNAs: a new class of breast cancer biomarkers
Mulrane, L., Klinger, R. W., McGee, S. F., Gallagher, W. M., & O’Connor, D. P. (2014) · Expert Review of Molecular Diagnostics · doi:10.1586/14737159.2014.901153 · Cited by 41
Gao, S., Wang, Y., Wang, M., Li, Z., Zhao, Z., Wang, R. X., Wu, R., Yuan, Z., Cui, R., Jiao, K., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.17816 · Cited by 41
Circulating miRNA in Atherosclerosis: A Clinical Biomarker and Early Diagnostic Tool
Sharma, A. R., Sharma, G., Bhattacharya, M., Lee, S., & Chakraborty, C. (2021) · Current Molecular Medicine · doi:10.2174/1566524021666210315124438 · Cited by 41
Biomimetic erythrocytes engineered drug delivery for cancer therapy
Zhang, W., Zhao, M., Gao, Y., Xu, C., Liu, X., Tang, S., Peng, Y., Wang, N., Hu, D., Peng, H., et al. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.133498 · Cited by 42
Circulating microRNAs as Promising Tumor Biomarkers
(2014) · Advances in Clinical Chemistry · doi:10.1016/bs.acc.2014.09.007 · Cited by 40
Classification of miRNA-Related Sequence Variations
Hrovatin, K., & Kunej, T. (2018) · Epigenomics · doi:10.2217/epi-2017-0126 · Cited by 40
Circulating non-coding RNA biomarkers of endocrine tumours
Butz, H., Patócs, A., & Igaz, P. (2024) · Nature Reviews Endocrinology · doi:10.1038/s41574-024-01005-8 · Cited by 39
High-Throughput Sequencing of Plasma MicroRNA in Chronic Fatigue Syndrome/Myalgic Encephalomyelitis
Brenu, E., Ashton, K. J., Batovska, J., Staines, D., & Marshall‐Gradisnik, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102783 · Cited by 41
Sensitive PCR-based quantitation of cell-free circulating microRNAs
Hastings, M. L., Palma, J., & Duelli, D. M. (2012) · Methods · doi:10.1016/j.ymeth.2012.07.026 · Cited by 39
Regulation of Gene Expression by Exercise-Related Micrornas
Masi, L. N., Serdan, T. D. A., Levada‐Pires, A. C., Hatanaka, E., Silveira, L. R., Cury‐Boaventura, M. F., Pithon‐Curi, T. C., Curi, R., Gorjão, R., & Hirabara, S. M. (2016) · Cellular Physiology and Biochemistry · doi:10.1159/000452507 · Cited by 39
Changes in miRNA in the lung and whole blood after whole thorax irradiation in rats
Gao, F., Liu, P., Narayanan, J., Yang, M., Fish, B. L., Liu, Y., Liang, M., Jacobs, E. R., & Medhora, M. M. (2017) · Scientific Reports · doi:10.1038/srep44132 · Cited by 39
Prediction of tissue-of-origin of early stage cancers using serum miRNomes
Matsuzaki, J., Kato, K., Oono, K., Tsuchiya, N., Sudo, K., Shimomura, A., Tamura, K., Shiino, S., Kinoshita, T., Daiko, H., et al. (2022) · JNCI Cancer Spectrum · doi:10.1093/jncics/pkac080 · Cited by 40
Exosomal ncRNAs in liquid biopsies for lung cancer
Hussain, M. S., Gupta, G., Ghaboura, N., Moglad, E. H. O., Almalki, W. H., Alzarea, S. I., Kazmi, I. A., Ali, H., MacLoughlin, R. J., Löebenberg, R., et al. (2024) · Clinica Chimica Acta · doi:10.1016/j.cca.2024.119983 · Cited by 39
MicroRNAs as Biomarkers of B-cell Lymphoma
Solé, C., Arnaiz, E., & Lawrie, C. H. (2018) · Biomarker Insights · doi:10.1177/1177271918806840 · Cited by 38
Kolenda, T., Guglas, K., Baranowski, D., Sobocińska, J., Kopczyńska, M., Teresiak, A., Bliźniak, R., & Lamperska, K. M. (2020) · Reports of Practical Oncology & Radiotherapy · doi:10.1016/j.rpor.2020.07.007 · Cited by 38
Raut, J. R., Schöttker, B., Holleczek, B., Guo, F., Bhardwaj, M., Miah, K., Schrotz‐King, P., & Brenner, H. (2021) · Nature Communications · doi:10.1038/s41467-021-25067-8 · Cited by 39
Novel Approach to Fecal Occult Blood Testing by Assay of Erythrocyte-Specific microRNA Markers
Wu, C. W., Cao, X., Berger, C. K., Foote, P. H., Mahoney, D. W., Simonson, J. A., Anderson, B. W., Yab, T. C., Taylor, W. R., Boardman, L. A., et al. (2017) · Digestive Diseases and Sciences · doi:10.1007/s10620-017-4627-6 · Cited by 37
A review of expression profiling of circulating microRNAs in men with prostate cancer
Kelly, B. D., Miller, N., Healy, N. A., Walsh, K., & Kerin, M. J. (2012) · British Journal of Urology · doi:10.1111/j.1464-410x.2012.11244.x · Cited by 37
Circulating miRNAs as Biomarkers of Acute Muscle Damage in Rats
Siracusa, J., Koulmann, N., Bourdon, S., Goriot, M., & Banzet, S. (2016) · American Journal Of Pathology · doi:10.1016/j.ajpath.2016.01.007 · Cited by 37
Serum MicroRNAs in HIV-Infected Individuals as Pre-Diagnosis Biomarkers for AIDS-NHL
Thapa, D. R., Hussain, S. K., Tran, W., DʼSouza, G., Bream, J. H., Achenbach, C. J., Ayyavoo, V., Detels, R., & Martı́nez-Maza, O. (2014) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0000000000000146 · Cited by 37
Ma, E., Fu, Y., & Garvey, W. T. (2018) · Metabolic Syndrome and Related Disorders · doi:10.1089/met.2017.0101 · Cited by 37
Zaporozhchenko, I. A., Morozkin, E. S., Ponomaryova, A. A., RYKOVA, E. Y., Чердынцева, Н. В., Zheravin, A. A., Pashkovskaya, O. A., Pokushalov, E. A., Vlassov, V. V., & Laktionov, P. P. (2018) · Scientific Reports · doi:10.1038/s41598-018-24769-2 · Cited by 37
Effect of plasma-derived extracellular vesicles on erythrocyte deformability in polymicrobial sepsis
Subramani, K., Raju, S. P., Chu, X., Warren, M., Pandya, C. D., Hoda, N., Fulzele, S., & Raju, R. P. (2018) · International Immunopharmacology · doi:10.1016/j.intimp.2018.10.011 · Cited by 37
Zhou, W., & Dimitriadis, E. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.586510 · Cited by 38
Tumor surveillance by circulating microRNAs: a hypothesis
Igaz, I., & Igaz, P. (2014) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-014-1682-4 · Cited by 37
Mensah, M., Borzi, C., Verri, C., Suatoni, P., Conte, D., Pastorino, U., Fortunato, O., Sozzi, G., & Boeri, M. (2017) · Journal of Visualized Experiments · doi:10.3791/56326 · Cited by 36
Wang, L., Li, S., Lee, M., Chou, M., Chou, W., Lee, S.-Y., Hsu, C., Huang, L., & Kuo, H. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00227 · Cited by 36
Orangi, E., & Motovali-Bashi, M. (2018) · Gene · doi:10.1016/j.gene.2018.11.036 · Cited by 36
Unbiased data analytic strategies to improve biomarker discovery in precision medicine
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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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