The DOI matches its Crossref record; 121 of the 127 references it cites were found in a registry or an index; 35 of the 64 sources its claims cite were checked for support.
Microfluidics: A New Tool for Modeling Cancer–Immune Interactions
Open accessAbstract
In recognition of the enormous potential of immunotherapies against cancer, research into the interactions between tumor and immune cells has accelerated, leading to the recent FDA approval of several drugs that reduce cancer progression. Numerous cellular and molecular interactions have been identified by which immune cells can intervene in the metastatic cascade, leading to the development of several in vivo and in vitro model systems that can recapitulate these processes. Among these, microfluidic technologies hold many advantages in terms of their unique ability to capture the essential features of multiple cell type interactions in three-dimensions while allowing tight control of the microenvironment and real-time monitoring. Here, we review current assays and discuss the development of new microfluidic technologies for immunotherapy.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
35 of 64 cited sources checked · 20 supported · 0 flagged · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Furthermore, cancer cells promoted macrophage proliferation[64].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Partly supportedcites [64] sourceExperimental — accuracy not yet measured
The Results (Cell morphological observations; page unavailable) show a macrophage migrating toward bladder cancer cells in the microfluidic device, and the Results (Arg-1 expression in macrophages; page unavailable) report increased Arg-1 expression. Neither passage establishes that cancer cells promoted macrophage proliferation; migration and activation are different outcomes. (LLM, conf=0.85)
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Recently, immunotherapies have shown promising results for reducing metastasis in melanoma or kidney cancer patients[1, 2].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic models: developing immunotherapies against metastasis
What the sources say
- Supportedcites [1] source
The opening section describes immunotherapy as producing durable, sometimes complete tumor regression in patients with metastatic melanoma and kidney cancer. This supports the citing sentence’s broad characterization of promising results for reducing metastatic disease. (LLM, conf=0.90)
- Partly supportedcites [2] sourceExperimental — accuracy not yet measured
In “Evidence of clinical activity for PD1 blockade” (page unavailable), the review describes promising tumour regressions and clinical responses in patients with melanoma and renal cancer, including patients with metastatic tumours. It does not establish that immunotherapy reduced the occurrence or spread of metastases, as distinct from treating existing cancer. (LLM, conf=0.82)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“They also showed that macrophages in co-culture expressed more Arginine-1, in an analogous manner to macrophage activation in the tumor microenvironment.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Could not verifycites [48] sourceExperimental — accuracy not yet measured
The Abstract and Results (‘Making up the experiment for data-drive’; page unavailable) describe co-culturing melanoma cells with mouse splenocytes and analyzing cell migration. Searches for Arginine-1, macrophage expression, and activation found no passage reporting increased Arginine-1 in co-cultured macrophages or comparing that response with activation in the tumor microenvironment. (LLM, conf=0.70)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Could not verify
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
“On one hand, there is evidence that immune cells have the capability to attenuate metastasis[54–59], which provides insight into how to restore or enhance their ability to combat cancer.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Not checked — no full text of the sourcecites [54] source
- Supportedcites [55] source
The Introduction reports that CD8+ T cells maintained dormancy of disseminated melanoma cells in visceral organs in the mouse model, and that depleting them accelerated tumor outgrowth. This supports the claim that immune cells can attenuate metastasis. (LLM, conf=0.94)
- Supportedcites [56] source
The paper reports that natural killer cells can inhibit metastasis in mice. In the passage labeled Abstract, mice receiving Cbl-b-deficient NK cells had fewer lung melanoma metastases, and the authors conclude that those NK cells inhibit the progression of lung and distant metastases. (LLM, conf=0.93)
- Supportedcites [57] source
The Results section, “Tumor entrained neutrophils inhibit seeding in the pre-metastatic lung” (page unavailable), reports that depleting neutrophils increased metastatic burden and produced about three times as many lung metastatic events in tumor-bearing mice. This supports the claim that immune cells can attenuate metastasis, specifically tumor-entrained neutrophils in this model. (LLM, conf=0.93)
- Not checked — no full text of the sourcecites [58]
- Supportedcites [59] source
The paper reports that anti-CD47 treatment increased macrophage phagocytosis of leiomyosarcoma cells, and the neoadjuvant-treatment results report that it almost completely inhibited lung metastases in mice. This supports the broad claim that immune cells can help attenuate metastasis, in the context of antibody treatment in a mouse model. (LLM, conf=0.90)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe cited sources support only part of this claim — read each source’s verdict below.
In the paper
“This is particularly important as there is growing evidence that cancer cells communicate with their microenvironment[29], specifically with organ-specific cells[30], resulting in organ-selectivity in metastasis[31].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Supportedcites [29] source
Citation [29] is attached to the claim that cancer cells communicate with their microenvironment, not to the later claims about organ-specific cells or organ-selectivity. The passage on paracrine signalling loops between cancer cells, macrophages and endothelial cells supports that claim (passage [4]; page not provided). (LLM, conf=0.91)
- Partly supportedcites [30] sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) invokes the seed-and-soil hypothesis to explain why tumors metastasize to particular organs. The Discussion (page unavailable) supports a narrower finding: breast cancer cells alter the brain microenvironment, which contributes to metastatic progression. The paper does not establish that communication with organ-specific cells causes organ selectivity across metastases. (LLM, conf=0.84)
- Not checked — no full text of the sourcecites [31] source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Studies have shown that dormancy can be induced by endothelial derived factors[24], thus demonstrating the need for microfluidic models that recapitulate interactions between ECs and tumor cells, using for example µVNs.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Supportedcites [24] source
The Introduction identifies endothelial-derived thrombospondin-1 as a tumor suppressor, and the Results report that endothelial cells induced sustained quiescence in breast cancer cells. The Discussion specifies that stable microvasculature induces this quiescence via thrombospondin-1. (LLM, conf=0.94)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“One of the major current limitations of in vitro metastatic models is their lack of organ-specificity[28].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Supportedcites [28] source
In “Cancer cell odyssey in the metastatic cascade,” the paper calls the lack of organ-specific in vitro models a significant limitation of current systems. The “Microfluidic tools for in vitro cancer models” section likewise says that the extravasation assays discussed lack organ specificity. (LLM, conf=0.94)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Recent studies are increasingly employing microvascular networks (µVNs)[21, 23, 24], where the permeability, architecture and diameters of vessels are more similar to those found in in vivo microvascular beds (Figure 2A) [21].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Partly supportedcites [21] sourceExperimental — accuracy not yet measured
The Introduction describes recent development of perfusable 3D microvascular networks with a more physiologically relevant configuration, and the Discussion says their permeability is comparable to that of in vivo venules. The Results describe self-organized vessels with 8–96 μm lumens, but our copy does not compare those diameters with in vivo microvascular beds. (LLM, conf=0.83)
- Partly supportedcites [23] sourceExperimental — accuracy not yet measured
The Discussion (page not specified in our copy) describes a branched, lumenized vessel network whose heterogeneous diameters and morphology resemble tumor vasculature in vivo. This supports the architectural comparison, but the paper does not establish that the network’s permeability or vessel diameters are more similar to those of in vivo microvascular beds. (LLM, conf=0.85)
- Partly supportedcites [24] sourceExperimental — accuracy not yet measured
The Results section reports that the authors grew robust three-dimensional microvascular networks, supporting this paper as an example of a study using such networks. Our copy does not establish that their vessels’ permeability, architecture, or diameters are more similar to in vivo microvascular beds, nor does it document an increasing trend in their use. No page number is available in the indexed passages. (LLM, conf=0.84)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Microfluidic assays have been designed to replicate certain aspects of several of these steps, such as EMT[13, 14], cancer cell invasion and adhesion[15–17], and intra-[18, 19] and extravasation[17, 20– 22] (see Text Box 3).”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Not checked — no full text of the sourcecites [13] source
- Not checked — no full text of the sourcecites [14] source
- Partly supportedcites [15] sourceExperimental — accuracy not yet measured
The Discussion describes a microfluidic system that models circulating breast cancer cells adhering to vascular endothelium under flow, supporting the adhesion part of the citation. It does not describe an assay that models cancer-cell invasion or extravasation. EMT and intravasation are attached to other citations in the citing sentence. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites [16] source
- Not checked — no full text of the sourcecites [17] source
- Supportedcites [18] sourceExperimental — accuracy not yet measured
The citation is attached to intravasation, not to the sentence’s examples of EMT, adhesion, or extravasation. The Results section describes a 3D microfluidic assay with an endothelial monolayer that permits observation of tumor-cell intravasation. (LLM, conf=0.94)
- Supportedcites [19] sourceExperimental — accuracy not yet measured
The citation to this paper is attached to intravasation, not to EMT, adhesion, or extravasation. The Metastasis chip design and Discussion sections describe a microfluidic assay that models cancer-cell intravasation into engineered microvessels. (LLM, conf=0.94)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe cited sources support only part of this claim — read each source’s verdict below.
In the paper
“These studies first showed that immune-deficient interferon regulatory factor-8 (IRF-8) knockout mice develop more tumors with less immune cell infiltration than wild type animals[50], and subsequently used a microfluidic assay to investigate the underlying mechanism in greater detail.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Partly supportedcites [50] sourceExperimental — accuracy not yet measured
The melanoma-growth section reports faster tumor growth and more lung metastatic foci in IRF-8 knockout mice, but does not establish that they developed more primary tumors. The immune-cell infiltration section reports fewer infiltrating T cells and dendritic cells in knockout tumors, while myeloid-derived suppressor cell infiltration was higher; the unqualified claim of less immune-cell infiltration misses that exception. (LLM, conf=0.85)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
- Borderline: one of the tests for a substantial claim is unclear. 1
- It may state two separate claims as one. 16
- Probably not a substantial claim. 8
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
“Specifically, they showed that immune spleen cells lacking IRF-8 do not migrate towards cancer cells, nor interact with them as efficiently as wild type immune cells[48–50], suggesting a mechanism to explain why IRF-8 knock-out cells fail to exert proper immune-surveillance leading to a heavier metastatic burden.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Supportedcites [48] source
The Abstract reports that only wild-type spleen cells established physical interactions with melanoma cells, while IRF-8 knockout cells showed poor reactivity. The Results (‘Making up the experiment for data-drive’) likewise report migration and clustering toward melanoma cells for wild-type cells, but no focused response by knockout cells. Page numbers are not provided in our copy. (LLM, conf=0.94)
- Not checked — no full text of the sourcecites [49] source
- Supportedcites [50] source
The Discussion reports that WT splenocytes crossed the microchannels toward the melanoma compartment, while IRF-8 KO cells were unable to move forward. The section on splenocyte migration also reports longer-lasting contact with melanoma cells for WT than IRF-8 KO splenocytes. The finding is supported in the paper’s B16.F10 melanoma microfluidic model. (LLM, conf=0.94)
Causal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesBorderline substantial claim. It is unclear whether the paper’s conclusions depend on it. It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Although it was first observed that immune cells play an anti-tumorigenic role, it was later realized they can be “educated” by cancer cells to become tolerant to tumors and even promote tumor growth and metastasis[37].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Supportedcites [37] source
The Abstract says the tumour microenvironment polarizes recruited macrophages into ‘tumour-educated’ cells that promote tumour progression and metastasis. The Immune escape section describes how tumours alter immune-cell functions to avoid immune rejection, supporting the claim about tolerance in substance. (LLM, conf=0.91)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“These µVNs represent a dramatic improvement over previous 2D extravasation models such as Boyden Transwell-chambers that consist of ECs seeded onto a permeable membrane inserted in a well-plate, since transwells do not allow for dynamic high resolution single cell imaging due to the long distance of the insert from the objective.”
- Also stated in: § Microfluidic: modeling the metastatic cascade · plain
“In addition, µVNs replicate better the 3D vessel architecture and endothelial barrier function [21].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Partly supportedcites [21] sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § Microfluidic: modeling the metastatic cascade · plain
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“While intravital imaging has proven extremely useful in the study of metastasis[6–7], it requires specialized expertise and equipment, and high image resolution is harder to attain in some visceral organs due to the depth of their location.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
What the sources say
- Not checked — no full text of the sourcecites [6] source
- Could not verifycites [7] sourceExperimental — accuracy not yet measured
The Introduction discusses expertise needed for microscopic inspection of plant pathogens, not intravital imaging. Searches for intravital imaging, metastasis, and depth-related limits on imaging visceral organs found no passage addressing the claim; page numbers are unavailable in our copy. (LLM, conf=0.78)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For example, neutrophils are known to assist with tumor cell extravasation following platelet aggregation around the tumor cell[60, 61].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Not checked — no full text of the sourcecites [60] source
- Partly supportedcites [61] sourceExperimental — accuracy not yet measured
The Results section ('Platelet-Derived TGFβ1 is Necessary for Metastasis In Vivo') reports tumor cells associated with platelets in blood vessels and evidence that platelet-derived TGFβ1 aids extravasation. Neither that passage nor the Discussion passages identify neutrophils as assisting extravasation; a search for 'neutrophils' found no supporting passage. Page numbers are unavailable in our copy. (LLM, conf=0.85)
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
Every source the paper cites for this claim was checked and supports it.
In the paper
“PDMS can also adsorb small hydrophobic molecules[9], which can be problematic for drug screening studies.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic vs. traditional models for cancer and metastasis research
What the sources say
- Supportedcites [9] source
The citation is attached to the claim that PDMS takes up small hydrophobic molecules. The Introduction (Hydrophobic absorption; page unavailable) describes their partitioning into PDMS, and the Discussion (page unavailable) reports a substantial reduction in medium estrogen. The paper calls this absorption into the polymer bulk rather than surface adsorption. (LLM, conf=0.88)
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Finally, future studies should analyze the role of several types of immune cells simultaneously, as their interplay has been shown to be critical for some steps of the metastatic cascade[60, 61].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Concluding Remarks
What the sources say
- Not checked — no full text of the sourcecites [60] source
- Partly supportedcites [61] sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) describes platelets shielding tumor cells from natural-killer-cell lysis, and the Discussion reports that platelet–tumor-cell signaling promotes metastatic seeding. These passages support a role for cellular interactions in metastasis, but they do not establish that interplay among several types of immune cells is critical to steps of the metastatic cascade. (LLM, conf=0.78)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“The immune cell response is a spatially orchestrated process, occurring in a variety of different tissues (i.e. bone marrow, blood stream and target tissue), which can be captured in microfluidic models through spatial compartmentalization.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
“Furthermore, some events of the metastatic cascade (e.g. intravasation) can be rare and thus difficult to image in vivobut this rate of occurrence can be more readily modulated in vitro.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic: modeling the metastatic cascade
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“This study showed that CM from macrophage and myofibroblasts increased the migration of cancer cells. Interestingly, tumor necrosis factor- α (TNF-α) produced by macrophages counteracted the migration-promoting effects of myofibroblasts.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Not checked — no full text of the sourcecites [51] source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
“Uniquely, the presence of microfluidic channels permits precise control of flow, allowing the study of many important biomechanical processes such as shear stress.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic vs. traditional models for cancer and metastasis research
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“For example, retrieving cells from microfluidic devices for subsequent biochemical studies is possible but not straightforward [6].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic vs. traditional models for cancer and metastasis research
What the sources say
- Not checked — no full text of the sourcecites [6] source
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
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
“We propose that microfluidics systems are particularly powerful tools to replicate the metastatic environment and should thus be exploited to study cancer-immune cell interactions.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidic models: developing immunotherapies against metastasis
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
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
“In addition, many immune cells exist under flow conditions in the bloodstream that can be uniquely recreated through precise control of flow in microfluidic systems.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Importantly, these studies demonstrated important differences between 2D and 3D, with tumor cells cultured in 3D spheroids showing a decreased production of TAA and HLA class I (as also observed in vivo)[47].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Microfluidics: modeling immune-cancer cell interactions
What the sources say
- Not checked — no full text of the sourcecites [47] source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
“Microfluidic systems offer the potential for high throughput, quantitative clinical analyses.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Outlook for future microfluidic applications in immunotherapy
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably 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
“Microfluidic systems are uniquely positioned to facilitate the development of personalized medicine because of the small number of cells needed from the patient and the potential to obtain rapid and automated results.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Outlook for future microfluidic applications in immunotherapy
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
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
“Microfluidic models can not only help characterize the immune-cancer cell interactions that have recently become interesting therapeutic targets, but also help in testing the efficacy of novel immunotherapies.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Concluding Remarks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Indeed, these current “lab-on-a-chip” models are intended to facilitate time-consuming bench-top procedures, but are, after all, still “chips-in-a-lab”[86] that require external equipment (e.g. pumps, microscope) and much human intervention.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Outlook for future microfluidic applications in immunotherapy
What the sources say
- Not checked — no full text of the sourcecites [86] source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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
“Eventually, microfluidic systems could represent an important intermediate step, bridging current in vitro high throughput screens and animal studies and human clinical trials.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Concluding Remarks
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
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
“Despite their tremendous experimental potential, to date, microfluidic studies have not been widely exploited to study cancer/immune cell interactions.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Outlook for future microfluidic applications in immunotherapy
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
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
“Thus, an opportunity exists to capitalize on the capability of microfluidic models to recapitulate interactions between cancer and immune cells as they occur in vivo, especially during metastatic spread.”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Concluding Remarks
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
In the paper
“Sackmann et al. estimated that 85% of microfluidic related publications are published in engineering, as opposed to clinical or biological journals, mostly as proof-of-principle studies[84].”
§ Microfluidics: A new tool for modeling cancer-immune interactions > Outlook for future microfluidic applications in immunotherapy
What the sources say
- Not checked — no full text of the sourcecites [84] source
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
No in vitro system, including microfluidic ones, can reproduce every aspect of in vivo complexity.
“Finally, care should be taken in extrapolating results from any in vitro study, including microfluidic ones, since they can never fully replicate all aspects of in vivo complexity.”
Citations
Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
The blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838 · cited 1×
“Recently, immunotherapies have shown promising results for reducing metastasis in melanoma or kidney cancer patients[1, 2].”
BackgroundThe origins and the future of microfluidics
Whitesides, G. M. (2006) · Nature · doi:10.1038/nature05058 · Cited by 9,687 · cited 1×
“Microfluidics is a rapidly expanding technology that relies on the use of small channels, ranging from tens to hundreds of micrometers in height or width for handling small fluid volumes[4].”
BackgroundMolecular Mechanisms of Stress-Responsive Changes in Collagen and Elastin Networks in Skin
Aziz, J., Shezali, H., Radzi, Z., Yahya, N. A., Abu Kassim, N. H., Czernuszka, J., & Rahman, M. T. (2016) · Skin Pharmacology and Physiology · doi:10.1159/000447017 · Cited by 7,323
Macrophage Diversity Enhances Tumor Progression and Metastasis
Qian, B., & Pollard, J. W. (2010) · Cell · doi:10.1016/j.cell.2010.03.014 · Cited by 5,338 · cited 1×
“Second, drug-resistance related problems are also minimized, since immune cells are less likely to acquire drug resistance than cancer cells[39].”
BackgroundThe pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited
Fidler, I. J. (2003) · Nature Reviews Cancer · doi:10.1038/nrc1098 · Cited by 4,686 · cited 1×
“This is particularly important as there is growing evidence that cancer cells communicate with their microenvironment[29], specifically with organ-specific cells[30], resulting in organ-selectivity in metastasis[31].”
BackgroundReconstituting organ-level lung functions on a chip
Huh, D., Matthews, B. D., Mammoto, A., Montoya-Zavala, M., Hsin, H. Y., & Ingber, D. E. (2010) · Science · doi:10.1126/science.1188302 · Cited by 4,250 · cited 1×
“, an airliquid interface for mimicking the pulmonary airways[34]).”
BackgroundDissemination and growth of cancer cells in metastatic sites
Chambers, A. F., Groom, A. C., & MacDonald, I. C. (2002) · Nature reviews. Cancer · doi:10.1038/nrc865 · Cited by 4,018 · cited 1×
“These steps include an epithelial-to-mesenchymal transition (EMT), invasion, intravasation, transport of circulating tumor cells (CTCs) in the bloodstream, extravasation in the distant organ, and recolonization at the metastatic site[12] (Fig.”
BackgroundMicroenvironmental regulation of metastasis
Joyce, J. A., & Pollard, J. W. (2009) · Nature Reviews Cancer · doi:10.1038/nrc2618 · Cited by 3,684 · cited 1×
“This is particularly important as there is growing evidence that cancer cells communicate with their microenvironment[29], specifically with organ-specific cells[30], resulting in organ-selectivity in metastasis[31].”
BackgroundThe present and future role of microfluidics in biomedical research
Sackmann, E. K., Fulton, A. L., & Beebe, D. J. (2014) · Nature · doi:10.1038/nature13118 · Cited by 2,995 · cited 3×
“estimated that 85% of microfluidic related publications are published in engineering, as opposed to clinical or biological journals, mostly as proof-of-principle studies[84].”
BackgroundMethod
Flagged first, then by citations
6 of the 127 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Organ-on-a-Chip: A New Paradigm for Drug Development
Ma, C., Peng, Y., Li, H., & Chen, W. (2020) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2020.11.009 · Cited by 612
Hoarau-Véchot, J., Rafii, A., Touboul, C., & Pasquier, J. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19010181 · Cited by 489
“If further analysis (Elisa, western blot) is required, the low cell number can also present a drawback [67].”
3D bioprinting for reconstituting the cancer microenvironment
Datta, P., Dey, M., Ataie, Z., Unutmaz, D., & Ozbolat, I. T. (2020) · npj Precision Oncology · doi:10.1038/s41698-020-0121-2 · Cited by 320
Personalized Cancer Medicine: An Organoid Approach
Es, H. A., Montazeri, L., Aref, A. R., Vosough, M., & Baharvand, H. (2018) · Trends in biotechnology · doi:10.1016/j.tibtech.2017.12.005 · Cited by 286
“In contrast to 2D cancer–immune interaction, in vitro 3D studies not only demonstrated decreased production of tumor-associated antigens in 3D models, but also highlighted the importance of using 3D tumor models in tumor immunology studies, which can be easily captured in microfluidic systems [64].”
BackgroundMoshksayan, K., Kashaninejad, N., Warkiani, M. E., Lock, J. G., Moghadas, H., Firoozabadi, B., Saidi, M. S., & Nguyen, N.-T. (2018) · Sensors and Actuators B: Chemical · doi:10.1016/j.snb.2018.01.223 · Cited by 267
“Other works have reviewed the importance of microfluidics in cancer cell culture and drug discovery [74-80], as well as considering various microfluidic chips enabling 3D cell culture with cancerous or noncancerous cells [9, 81-86].”
BackgroundTargeting immune cells for cancer therapy
Gun, S. Y., Lee, S. W. L., Sieow, J. L., & Wong, S. C. (2019) · Redox Biology · doi:10.1016/j.redox.2019.101174 · Cited by 237
Self-citationOrgan-on-chip models of cancer metastasis for future personalized medicine: From chip to the patient
Caballero, D., Kaushik, S., Correlo, V. M., Oliveira, J. M., Reis, R. L., & Kundu, S. C. (2017) · Biomaterials · doi:10.1016/j.biomaterials.2017.10.005 · Cited by 221
A role for microfluidic systems in precision medicine
Ayuso, J. M., Virumbrales-Muñoz, M., Lang, J. M., & Beebe, D. J. (2022) · Nature Communications · doi:10.1038/s41467-022-30384-7 · Cited by 219
Organ-on-a-Chip for Cancer and Immune Organs Modeling
Sun, W., Luo, Z., Lee, J., Kim, H., Lee, K., Tebon, P., Feng, Y., Dokmeci, M. R., Sengupta, S., & Khademhosseini, A. (2019) · Advanced Healthcare Materials · doi:10.1002/adhm.201801363 · Cited by 221
Dynamic interplay between tumour, stroma and immune system can drive or prevent tumour progression
Seager, R. J., Hajal, C., Spill, F., Kamm, R. D., & Zaman, M. H. (2017) · Convergent Science Physical Oncology · doi:10.1088/2057-1739/aa7e86 · Cited by 192
“The mechanical properties of the ECM have a significant effect on cancer dissemination and immune cell-cancer cell interactions, and furthermore, immune cells have been shown to play a role in various steps of the metastatic cascade, from cancer cell detachment and dissemination from the primary tumour, to their arres…”
Self-citationParlato, S., De Ninno, A., Molfetta, R., Toschi, E., Salerno, D., Mencattini, A., Romagnoli, G., Fragale, A., Roccazzello, L., Buoncervello, M., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-01013-x · Cited by 181
Ayuso, J. M., Rehman, S., Virumbrales-Muñoz, M., McMinn, P. H., Geiger, P. G., Fitzgerald, C., Heaster, T. M., Skala, M. C., & Beebe, D. J. (2021) · Science Advances · doi:10.1126/sciadv.abc2331 · Cited by 174
“Therefore, the development of new tools that allow researchers to decipher the complex mechanisms driving immune exhaustion could accelerate the development of next-generation immunotherapies (12).”
BackgroundThe effects of monocytes on tumor cell extravasation in a 3D vascularized microfluidic model
Boussommier-Calleja, A., Atiyas, Y., Haase, K., Headley, M., Lewis, C., & Kamm, R. D. (2019) · Biomaterials · doi:10.1016/j.biomaterials.2018.03.005 · Cited by 158
“We have established microfluidic devices as a unique and powerful platform for studying immune and cancer cell dynamics, in particular during the metastatic cascade[23].”
MethodSelf-citationTumor organoid models in precision medicine and investigating cancer-stromal interactions
Xu, R., Zhou, X., Wang, S., & Trinkle, C. (2021) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2020.107668 · Cited by 134
Endothelial Regulation of Drug Transport in a 3D Vascularized Tumor Model
Haase, K., Offeddu, G. S., Gillrie, M. R., & Kamm, R. D. (2020) · Advanced Functional Materials · doi:10.1002/adfm.202002444 · Cited by 126
Self-citationMicroengineered cancer-on-a-chip platforms to study the metastatic microenvironment
Lara, R. P., & Annabi, N. (2016) · Lab on a Chip · doi:10.1039/c6lc00718j · Cited by 130
Applications of tumor chip technology
Hachey, S. J., & Hughes, C. C. W. (2018) · Lab on a Chip · doi:10.1039/c8lc00330k · Cited by 128
Applications of Microfluidics and Organ-on-a-Chip in Cancer Research
Regmi, S., Poudel, C., Adhikari, R., & Luo, K. Q. (2022) · Biosensors · doi:10.3390/bios12070459 · Cited by 137
Brain-on-a-chip: A history of development and future perspective
Bang, S., Jeong, S., Choi, N., & Kim, H. N. (2019) · Biomicrofluidics · doi:10.1063/1.5120555 · Cited by 117
Tumor Cell Dormancy: Threat or Opportunity in the Fight against Cancer
Jahanban-Esfahlan, R., Seidi, K., Manjili, M. H., Jahanban-Esfahlan, A., Javaheri, T., & Zare, P. (2019) · Cancers · doi:10.3390/cancers11081207 · Cited by 111
Characterizing the role of monocytes in T cell cancer immunotherapy using a 3d microfluidic model
Lee, S. W. L., Adriani, G., Ceccarello, E., Pavesi, A., Tan, A. T., Bertoletti, A., Kamm, R. D., & Wong, S. C. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00416 · Cited by 109
“Prompted by our null observations in a 2D system, we moved toward a 3D microfluidic tumor model, which, among several other advantages, is a physiological improvement from the 2D in vitro system (43, 45).”
MethodSelf-citationKuo, C., Wang, J.-Y., Lin, Y., Wo, A. M., Chen, B. P. C., & Lee, H. (2017) · Scientific Reports · doi:10.1038/s41598-017-04718-1 · Cited by 106
Wang, X., Sun, Q., & Pei, J. (2018) · Micromachines · doi:10.3390/mi9100493 · Cited by 106
“Besides the anti-angiogenic therapies, immunotherapies against cancer have shown enormous potential, leading to the recent FDA approval of several drugs that reduce cancer progression [138].”
BackgroundModeling Nanocarrier Transport across a 3D In Vitro Human Blood‐Brain–Barrier Microvasculature
Lee, S. W. L., Campisi, M., Osaki, T., Possenti, L., Mattu, C., Adriani, G., Kamm, R. D., & Chiono, V. (2020) · Advanced Healthcare Materials · doi:10.1002/adhm.201901486 · Cited by 107
Self-citationDrug screening in 3D in vitro tumor models: overcoming current pitfalls of efficacy read‐outs
Santo, V. E., Rebelo, S. P., Estrada, M. F., Alves, P. M., Boghaert, E. R., & Brito, C. (2016) · Biotechnology Journal · doi:10.1002/biot.201600505 · Cited by 110
“Therefore, these microfluidic models constitute ideal setups to test libraries of compounds and biological formulations [112].”
BackgroundAdvanced model systems and tools for basic and translational human immunology
Wagar, L. E., DiFazio, R. M., & Davis, M. M. (2018) · Genome Medicine · doi:10.1186/s13073-018-0584-8 · Cited by 104
Towards the development of human immune-system-on-a-chip platforms
Polini, A., del Mercato, L. L., Adriano Barra, A., Zhang, Y. S., Calabi, F., & Gigli, G. (2018) · Drug Discovery Today · doi:10.1016/j.drudis.2018.10.003 · Cited by 101
3D cancer models: One step closer to in vitro human studies
Manduca, N., Maccafeo, E., Maria, R. D., Sistigu, A., & Musella, M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1175503 · Cited by 103
Microphysiological Systems: Design, Fabrication, and Applications
Wang, K., Man, K., Liu, J., Liu, Y., Chen, Q., Zhou, Y., & Yang, Y. S. (2020) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.9b01667 · Cited by 86
Immunocompetent cancer-on-chip models to assess immuno-oncology therapy
Maulana, T. I., Kromidas, E., Wallstabe, L., Cipriano, M., Alb, M., Zaupa, C., Hudecek, M., Fogal, B., & Loskill, P. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.03.015 · Cited by 86
In Vitro Modeling of Mechanics in Cancer Metastasis
Malandrino, A., Kamm, R. D., & Moeendarbary, E. (2017) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.7b00041 · Cited by 78
Self-citationIn vitro models of molecular and nano-particle transport across the blood-brain barrier
Hajal, C., Campisi, M., Mattu, C., Chiono, V., & Kamm, R. D. (2018) · Biomicrofluidics · doi:10.1063/1.5027118 · Cited by 79
Self-citationA microfluidic platform for drug screening in a 3D cancer microenvironment
Pandya, H. J., Dhingra, K., Prabhakar, D., Chandrasekar, V., Natarajan, S. K., Vasan, A. S., Kulkarni, A., & Shafiee, H. (2017) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2017.03.054 · Cited by 76
“In the past decade, microfluidics has shown a great promise in developing tools for cancer research (Mukhopadhyay, 2007; Calleja et al., 2016; Wlodkowic and Cooper, 2010).”
BackgroundYang, Y., Hu, Y., & Wang, H. (2016) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2016/5274084 · Cited by 76
“Given its advantages of high-throughput feature, controllable tumor growth for standardization, and patient-derived cell growth allowing for personalized medicine [119–121], in vitro 3D tissue model by tissue engineering technology such as microfluidic technique could be a powerful alternative approach for the study o…”
BackgroundHow single-cell immunology is benefiting from microfluidic technologies
Jammes, F., & Maerkl, S. J. (2020) · Microsystems & Nanoengineering · doi:10.1038/s41378-020-0140-8 · Cited by 73
Ronteix, G., Jain, S., Angély, C., Cazaux, M., Khazen, R., Bousso, P., & Baroud, C. N. (2022) · Nature Communications · doi:10.1038/s41467-022-30575-2 · Cited by 71
“(11), (12), and (13), provides a formula for λin(n): λinðnÞ 1⁄4 logð1 pn;nþ1Þ ðN nÞΔt : ð14Þ”
Beer, M., Kuppalu, N., Stefanini, M., Becker, H., Schulz, I., Manoli, S., Schuette, J., Schmees, C., Casazza, A., Stelzle, M., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-01256-8 · Cited by 75
Emerging approaches to study cell-cell interactions in tumor microenvironment
Nishida‐Aoki, N., & Gujral, T. S. (2019) · Oncotarget · doi:10.18632/oncotarget.26585 · Cited by 76
“These microchambers allow observation of real-time and 3D immune-cancer cell interactions [75], cell behavior in metastatic cascades, such as EMT, invasion and adhesion for intra-and extravasation [76].”
BackgroundLucarini, V., Buccione, C., Ziccheddu, G., Peschiaroli, F., Sestili, P., Puglisi, R., Mattia, G., Zanetti, C., Parolini, I., Bracci, L., et al. (2016) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2016.08.024 · Cited by 73
Microfluidic Systems for Cancer Diagnosis and Applications
Akgönüllü, S., Bakhshpour, M., Pişkin, A. K., & Deni̇zli̇, A. (2021) · Micromachines · doi:10.3390/mi12111349 · Cited by 76
“A variety of in vivo, ex vivo, and in vitro experimental models have been traditionally used to discover therapeutic targets and test novel drugs for cancer [55].”
BackgroundMethodInflammation-on-a-Chip: Probing the Immune System Ex Vivo
Irimia, D., & Wang, X. (2018) · Trends in biotechnology · doi:10.1016/j.tibtech.2018.03.011 · Cited by 74
Ekert, J. E., Deakyne, J., Pribul-Allen, P., Terry, R., Schofield, C., Jeong, C. G., Storey, J., Mohamet, L., Francis, J., Naidoo, A., et al. (2020) · SLAS DISCOVERY · doi:10.1177/2472555220923332 · Cited by 68
Advanced technological tools to study multidrug resistance in cancer
Andrei, L., Kasas, S., Ochoa, I., Stanković, T., Korsnes, M. S., Václavíková, R., Assaraf, Y. G., & Pešić, M. (2019) · Drug Resistance Updates · doi:10.1016/j.drup.2019.100658 · Cited by 68
“several approaches using different microfluidic devices to mimic the immune-cancer interactions were developed (Boussommier-Calleja et al., 2016).”
BackgroundBiomechanical Contributions to Macrophage Activation in the Tumor Microenvironment
Hoffmann, E. J., & Ponik, S. M. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00787 · Cited by 68
Microfluidics meets 3D cancer cell migration
Mehta, P., Rahman, Z., ten Dijke, P., & Boukany, P. E. (2022) · Trends in cancer · doi:10.1016/j.trecan.2022.03.006 · Cited by 78
Kumar, V., & Varghese, S. (2018) · Advanced Healthcare Materials · doi:10.1002/adhm.201801198 · Cited by 73
A 3D toolbox to enhance physiological relevance of human tissue models
Picollet-D’hahan, N., Dolega, M. E., Liguori, L., Marquette, C., Le Gac, S., Gidrol, X., & Martin, D. K. (2016) · Trends in Biotechnology · doi:10.1016/j.tibtech.2016.06.012 · Cited by 65
Tumor-on-a-chip platforms to study cancer–immune system crosstalk in the era of immunotherapy
Parlato, S., Grisanti, G., Sinibaldi, G., Peruzzi, G., Casciola, C. M., & Gabriele, L. (2020) · Lab on a Chip · doi:10.1039/d0lc00799d · Cited by 69
Saha, B., Mathur, T., Handley, K. F., Hu, W., Afshar-Kharghan, V., Sood, A. K., & Jain, A. (2020) · Blood Advances · doi:10.1182/bloodadvances.2020001632 · Cited by 63
“hypotheses and dissect the events underlying human platelet extravasation with animal models is not easily possible.(12) For example, determining vascular alterations near cancer tissue over time is extremely challenging, and differential tissue and cell effluents cannot be continually collected for downstream genetic…”
BackgroundNew Advances in the Study of Bone Tumors: A Lesson From the 3D Environment
Cortini, M., Baldini, N., & Avnet, S. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.00814 · Cited by 65
Lee, S. W. L., Seager, R. J., Litvak, F., Spill, F., Sieow, J. L., Leong, P. H., Kumar, D., Tan, A. S. M., Wong, S. C., Adriani, G., et al. (2020) · Integrative Biology · doi:10.1093/intbio/zyaa007 · Cited by 60
Self-citationDegradation of extracellular matrix regulates osteoblast migration: A microfluidic-based study
Movilla, N., Borau, C., Valero, C., & García‐Aznar, J. M. (2017) · Bone · doi:10.1016/j.bone.2017.10.025 · Cited by 62
Screening Cancer Immunotherapy: When Engineering Approaches Meet Artificial Intelligence
Zhou, X., Qu, M., Tebon, P. J., Jiang, X., Wang, C., Xue, Y., Zhu, J., Zhang, S., Öklü, R., Sengupta, S., et al. (2020) · Advanced Science · doi:10.1002/advs.202001447 · Cited by 55
Microfluidic modeling of the biophysical microenvironment in tumor cell invasion
Huang, Y., Segall, J. E., & Wu, M. (2017) · Lab on a Chip · doi:10.1039/c7lc00623c · Cited by 58
Tumor Microenvironment and Hydrogel-Based 3D Cancer Models for In Vitro Testing Immunotherapies
Vitale, C., Marzagalli, M., Scaglione, S., Dondero, A., Bottino, C., & Castriconi, R. (2022) · Cancers · doi:10.3390/cancers14041013 · Cited by 56
“Interestingly, at this time, the majority of these microfluidic devices are adopted for co-culturing tumor–immune cells in different compartments, physically separated by a polymeric gel, for evaluating the real-time cell migration under virtual static conditions, similar to the Boyden chamber-based assays [204,206,20…”
BackgroundMethodInfluentialJain, K. K. (2020) · Medical Principles and Practice · doi:10.1159/000511107 · Cited by 53
Macaraniag, C., Luan, Q., Zhou, J., & Papautsky, I. (2022) · APL Bioengineering · doi:10.1063/5.0093806 · Cited by 47
Mitxelena-Iribarren, O., Zabalo, J., Arana, S., & Mujika, M. (2019) · Biosensors & bioelectronics · doi:10.1016/j.bios.2018.09.001 · Cited by 44
Critical Considerations for the Design of Multi-Organ Microphysiological Systems (MPS)
Malik, M., Yang, Y., Fathi, P., Mahler, G. J., & Esch, M. B. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.721338 · Cited by 43
Flourishing tumor organoids: History, emerging technology, and application
Yang, Q., Li, M., Yang, X., Xiao, Z., Tong, X., Tuerdi, A., Li, S., & Lei, L. (2023) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10559 · Cited by 46
Fluid flow to mimic organ function in 3D in vitro models
Juste-Lanas, Y., Hervás-Raluy, S., García‐Aznar, J. M., & González‐Loyola, A. (2023) · APL Bioengineering · doi:10.1063/5.0146000 · Cited by 53
Assessing personalized responses to anti-PD-1 treatment using patient-derived lung tumor-on-chip
Veith, I., Nurmik, M., Mencattini, A., Damei, I., Lansche, C., Brosseau, S., Gropplero, G., Corgnac, S., Filippi, J., Poté, N., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101549 · Cited by 49
“3,5 For example, we previously showed that a specific immune response, antibody-dependent cell-mediated cytotoxicity, can be recapitulated in a HER2 + breast ToC treated with trastuzumab (Herceptin).”
BackgroundOncoimmunology Meets Organs-on-Chip
Mattei, F., Andreone, S., Mencattini, A., Ninno, A. D., Businaro, L., Martinelli, E., & Schiavoni, G. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.627454 · Cited by 48
“Thus, OOC systems can be classified as advanced in vitro smart platforms evolved from in vitro and in vivo scientific knowledge (Boussommier-Calleja et al., 2016).”
BackgroundTan, S. Y., Leung, Z., & Wu, A. R. (2020) · Small · doi:10.1002/smll.201905055 · Cited by 46
Microphysiological systems for solid tumor immunotherapy: opportunities and challenges
Abizanda-Campo, S., Virumbrales-Muñoz, M., Humayun, M., Mármol, I., Beebe, D. J., Ochoa, I., Oliván, S., & Ayuso, J. M. (2023) · Microsystems & Nanoengineering · doi:10.1038/s41378-023-00616-x · Cited by 42
Microfluidic system for modelling 3D tumour invasion into surrounding stroma and drug screening
Du, Z., Mi, S., Yi, X., Xu, Y., & Sun, W. (2018) · Biofabrication · doi:10.1088/1758-5090/aac70c · Cited by 42
Ayensa-Jiménez, J., Pérez-Aliacar, M., Ranđelović, T., Oliván, S., Fernández, L. J., Sanz‐Herrera, J. A., Ochoa, I., Doweidar, M. H., & Doblaré, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-78215-3 · Cited by 40
Incorporating Tumor-Associated Macrophages into Engineered Models of Glioma
Akins, E. A., Aghi, M. K., & Kumar, S. (2020) · iScience · doi:10.1016/j.isci.2020.101770 · Cited by 43
“platforms have proven useful for studying cell migration, angiogenesis and other cancer-associated phenomena, and are increasingly being leveraged to model cancerimmune cell interactions (Boussommier-Calleja et al., 2016; Ma et al., 2018; Sung and Beebe, 2014).”
BackgroundRingquist, R., Ghoshal, D., Jain, R., & Roy, K. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.114003 · Cited by 39
Ravi, K., Manoharan, T. J. M., Wang, K.-C., Pockaj, B. A., & Nikkhah, M. (2023) · Biomaterials · doi:10.1016/j.biomaterials.2023.122428 · Cited by 45
Offeddu, G. S., Cambria, E., Shelton, S. E., Haase, K., Wan, Z., Possenti, L., Nguyen, H. T., Gillrie, M. R., Hickman, D., Knutson, C. G., et al. (2024) · Advanced Science · doi:10.1002/advs.202402757 · Cited by 44
Self-citationDhiman, N., Shagaghi, N., Bhave, M. R., Sümer, H., Kingshott, P., & Rath, S. N. (2020) · Cytotherapy · doi:10.1016/j.jcyt.2020.07.004 · Cited by 36
Going with the Flow: Modeling the Tumor Microenvironment Using Microfluidic Technology
Xie, H., Appelt, J. W., & Jenkins, R. W. (2021) · Cancers · doi:10.3390/cancers13236052 · Cited by 41
Organoids Provide an Important Window on Inflammation in Cancer
Baker, K. (2018) · Cancers · doi:10.3390/cancers10050151 · Cited by 37
Tissues and Tumor Microenvironment (TME) in 3D: Models to Shed Light on Immunosuppression in Cancer
Ho, T., & Msallam, R. (2021) · Cells · doi:10.3390/cells10040831 · Cited by 39
Modeling the Leukemia Microenviroment In Vitro
Scielzo, C., & Ghia, P. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.607608 · Cited by 35
“Many models recently developed include vasculature components that allow angiogenesis and migration (48).”
BackgroundMethodChen, S.-C., Wu, P.-C., Wang, C.-Y., & Kuo, P.-L. (2020) · Scientific Reports · doi:10.1038/s41598-020-70694-8 · Cited by 32
Hot or cold: Bioengineering immune contextures into in vitro patient-derived tumor models
Too, N. S. H., Ho, N. C. W., Adine, C., Iyer, N. G., & Fong, E. L. S. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.05.001 · Cited by 32
Towards in silico Models of the Inflammatory Response in Bone Fracture Healing
Lafuente-Gracia, L., Borgiani, E., Nasello, G., & Geris, L. (2021) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.703725 · Cited by 39
Engineered fluidic systems to understand lymphatic cancer metastasis
Greenlee, J. D., & King, M. R. (2020) · Biomicrofluidics · doi:10.1063/1.5133970 · Cited by 31
Trends in Bone Metastasis Modeling
Laranga, R., Duchi, S., Ibrahim, T., Guerrieri, A. N., Donati, D. M., & Lucarelli, E. (2020) · Cancers · doi:10.3390/cancers12082315 · Cited by 31
“Furthermore, microfluidic systems have also been studied in detail to better recapitulate the cancer cell–immune cell interactions, with the ultimate aim of increasing knowledge on cancer immunotherapies [125].”
BackgroundMoghaddam, F. D., Anvar, A., Ilkhani, E., Dadgar, D., Rafiee, M., Ranjbaran, N., Mortazavi, P., Ghoreishian, S. M., Huh, Y. S., & Makvandi, P. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02479-4 · Cited by 37
“A primary challenge is the accurate simulation of the intricate interactions within the immune sys-tem which encompasses a variety of cell types, signaling pathways, and inflammatory responses [204].”
Dhiman, N., Shagaghi, N., Bhave, M. R., Sümer, H., Kingshott, P., & Rath, S. N. (2020) · Advanced Biosystems · doi:10.1002/adbi.201900285 · Cited by 29
Designing Hydrogel-Based Bone-On-Chips for Personalized Medicine
Nasello, G., Cóndor, M., Vaughan, T. J., & Schiavi, J. (2021) · Applied Sciences · doi:10.3390/app11104495 · Cited by 29
“Yet, traditional 2D in vitro models are not suitable for long-term studies and may fail in recapitulating a clinically relevant environment due to the absence of all factors present in vivo [9], but their high output and outcome balance this weakness.”
BackgroundIn Vitro Modeling of Tumor–Immune System Interaction
Mengus, C., Muraro, M. G., Mele, V., Amicarella, F., Manfredonia, C., Foglietta, F., Muenst, S. E., Soysal, S. D., Iezzi, G., & Spagnoli, G. C. (2017) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.7b00077 · Cited by 32
Manoharan, T. J. M., Ravi, K., Suresh, A. P., Acharya, A. P., & Nikkhah, M. (2024) · Advanced Healthcare Materials · doi:10.1002/adhm.202303658 · Cited by 27
Microfluidic Tumor Vasculature Model to Recapitulate an Endothelial Immune Barrier Expressing FasL
Kim, S., Park, J., Kim, J., & Jeon, J. S. (2021) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.0c01542 · Cited by 27
Huang, R., Li, S., Tian, C., et al. (2022) · British Journal of Cancer · doi:10.1038/s41416-022-01896-2 · Cited by 26
“In addition, we applied a set of 3D-culturing chips devised by MIT researchers [50] to the cellular invasion assay.”
MethodEmerging trends in modeling human liver disease in vitro
Underhill, G. H., & Khetani, S. R. (2019) · APL Bioengineering · doi:10.1063/1.5119090 · Cited by 26
Anti-Cancer Drug Screening with Microfluidic Technology
Monjezi, M., Rismanian, M., Jamaati, H., & Kashaninejad, N. (2021) · Applied Sciences · doi:10.3390/app11209418 · Cited by 28
“Microfluidic technology has various potential applications in cancer research, including drug screening, drug discovery, immunotherapy, and clinical oncology [1,2].”
BackgroundRecent advances in microfluidic models for cancer metastasis research
Xu, H. M., Liu, X., & Le, W. (2018) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2018.04.007 · Cited by 25
Miedel, M. T., Gavlock, D. C., Jia, S., Gough, A., Taylor, D. L., & Stern, A. M. (2019) · Scientific Reports · doi:10.1038/s41598-019-44756-5 · Cited by 24
Nuts and Bolts: Microfluidics for the Production of Biomaterials
Fontana, F., Martins, J. P., Torrieri, G., & Santos, H. A. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201800611 · Cited by 25
Beelen, N. A., Aberle, M. R., Bruno, V., Damink, S. W. M. O., Bos, G. M. J., Rensen, S. S., & Wieten, L. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1133796 · Cited by 26
Use and application of organ-on-a-chip platforms in cancer research
Yu, Y., Zhou, T., & Cao, L.-L. (2023) · Journal of Cell Communication and Signaling · doi:10.1007/s12079-023-00790-7 · Cited by 28
“In vitro studies have demonstrated that the production of tumor-associated antigens is decreased in 3D models compared with that in 2D models, and the advantages of 3D models in tumor immunity research are clearly highlighted in microfluidic systems (Boussommier-Calleja et al. 2016).”
BackgroundAlves, C. L., Deng, Z., Kermeci, N., & Shih, S. C. C. (2024) · Lab on a Chip · doi:10.1039/d3lc01090b · Cited by 22
Structural colour enhanced microfluidics
Qin, D., Gibbons, A. H., Ito, M. M. M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29956-4 · Cited by 21
Fan, Y., Xu, C., Deng, N., Gao, Z., Jiang, Z., Li, X., Zhou, Y., Pei, H., Li, L., & Tang, B. (2023) · Lab on a Chip · doi:10.1039/d2lc01077a · Cited by 21
Emerging Strategies in 3D Culture Models for Hematological Cancers
Barozzi, D., & Scielzo, C. (2023) · HemaSphere · doi:10.1097/hs9.0000000000000932 · Cited by 22
Modeling the tumor immune microenvironment for drug discovery using 3D culture
Lee, J. Y., & Chaudhuri, O. (2021) · APL Bioengineering · doi:10.1063/5.0030693 · Cited by 22
Metadata
- Authors
- Boussommier-Calleja, A., Li, R., Chen, M. B., Wong, S. C., & Kamm, R. D.
- Affiliations
- Massachusetts Institute of Technology (US)
- Agency for Science, Technology and Research (SG)
- Corresponding author
- Kamm, Roger D.
- Venue
- Trends in Cancer
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 2
- Issue
- 1
- Pages
- 6-19
- ISSN
- 2405-8025 (ISSN-L)
- 2405-8033
- PMC
- PMC4743529
- OpenAlex
- W2279226389
- Cited by
- 224
- References
- 127
- Citations by year
- 2026: 11 · 2025: 26 · 2024: 18 · 2023: 24 · 2022: 23 · 2021: 24 · 2020: 34 · 2019: 17 · 2018: 24 · 2017: 16 · 2016: 6
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Trends in cancer (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-nd)
- Funders
- Cancer Research Institute
- National Cancer Institute (R33CA174550, U01CA202177)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Capillary Electrophoresis Applications
- Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Bio-sensing Technologies
- Keywords
- microfluidics, tumor-immune interactions, tumor microenvironment, immunotherapy, metastasis, tumor-immune cell interactions, 3D cell culture, in vitro model, real-time monitoring, microfluidic assay
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 2026-09-28, under version 3 of the claim definition (prompt extract-v3).
A second model labelled each claim on 2026-09-28 (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 ›
Are you an author, or do you see a problem with this page? Request a review
