B cells and tertiary lymphoid structures promote immunotherapy response
Open accessAbstract
Treatment with immune checkpoint blockade (ICB) has revolutionized cancer therapy. Until now, predictive biomarkers 1-10 and strategies to augment clinical response have largely focused on the T cell compartment. However, other immune subsets may also contribute to anti-tumour immunity 11-15, although these have been less well-studied in ICB treatment 16. A previously conducted neoadjuvant ICB trial in patients with melanoma showed via targeted expression profiling 17 that B cell signatures were enriched in the tumours of patients who respond to treatment versus non-responding patients. To build on this, here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders. Our findings were corroborated using a computational method (MCP-counter 18) to estimate the immune and stromal composition in this and two other ICB-treated cohorts (patients with melanoma and renal cell carcinoma). Histological evaluation highlighted the localization of B cells within tertiary lymphoid structures. We assessed the potential functional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal expansion and unique functional states of B cells in responders. Mass cytometry showed that switched memory B cells were enriched in the tumours of responders. Together, these data provide insights into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.
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- Findingcitation
The findings were corroborated in translational studies of separate melanoma and sarcoma cohorts treated with ICB.
“Moreover, these findings were corroborated in translational studies of separate cohorts of patients with melanoma36 and sarcoma37 who were treated with ICB.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [36] Cabrita, R. L. et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature https://doi.org/10.1038/s41586-019-1914-8 (2020). source
Not checked in the free run.
- cites [37] Petitprez, F. et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature https://doi.org/10.1038/s41586-019-1906-8 (2020). source
Not checked in the free run.
- Findingcitation
B cells were not significantly associated with pathological response rates in a trial of neoadjuvant targeted therapy in BRAF-mutated melanoma.
“B cells were not significantly associated with pathological response rates in an analogous trial of neoadjuvant-targeted therapy in patients with BRAF-mutated melanoma38”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [38] Amaria, R. N. et al. Neoadjuvant plus adjuvant dabrafenib and trametinib versus standard of care in patients with high-risk, surgically resectable melanoma: a single-centre, open-label, randomised, phase 2 trial. Lancet Oncol. 19, 181–193 (2018). source
Not checked in the free run.
- Findingcitation
High B cell lineage scores in responders were replicated in an additional melanoma cohort (OpACIN-neo) treated with neoadjuvant versus adjuvant checkpoint blockade (n = 12 responders, 6 non-responders).
“Findings of high B cell lineage scores in responders were replicated in samples from an additional cohort of patients with melanoma treated with neoadjuvant versus adjuvant checkpoint blockade (ClinicalTrials.gov identifier NCT02437279, OpACIN-neo trial) (n = 12 responders, 6 non-responders)35”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [35] Blank, C. U. et al. Neoadjuvant versus adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma. Nat. Med. 24, 1655–1661 (2018). source
Not checked in the free run.
- Findingown data
B cell signatures alone predicted response in univariable analyses (odds ratio 2.6, P = 0.02 for the trial; odds ratio 2.9, P = 0.03 for combined melanoma cohorts).
“B cell signatures alone were predictive of response in univariable analyses (odds ratio 2.6, P = 0.02 for our trial, and odds ratio 2.9, P = 0.03 for combined melanoma cohorts)”
Quote in the paperSubstantial claim - Findingown data
B cell signatures did not predict response in multivariable analyses when other components of the immune cell infiltrate were considered.
“but not in multivariable analyses when considering other components of the immune cell infiltrate”
Quote in the paperSubstantial claim
- Findingown data
MCP-counter analysis of RNA-seq data showed enrichment of a B cell signature in responders versus non-responders at baseline and early on-treatment (P = 0.036 and 0.038, respectively).
“In these analyses, we again observed enrichment of a B cell signature in responders versus non-responders at baseline and early on-treatment (P = 0.036 and 0.038, respectively).”
Quote in the paperSubstantial claim - Findingown data
In the RCC pre-surgical ICB trial, baseline tumour samples showed significantly higher expression of B-cell-related genes in responders versus non-responders (P = 0.0011, n = 17 responders and 11 non-responders).
“Gene expression profiling by microarray and subsequent MCP-counter analysis of baseline tumour samples was performed, demonstrating significantly higher expression of B-cell-related genes in responders versus non-responders (P = 0.0011, n = 17 responders and 11 non-responders)”
Quote in the paperSubstantial claim - Findingown data
Genes expected to alter B cell function, including FCRL5, IDO1, IFNG, and BTLA, were significantly enriched in responders compared with non-responders.
“Other genes that are expected to alter the function of B cells were also significantly enriched in responders versus non-responders, such as FCRL5, IDO1, IFNG and BTLA.”
Quote in the paperSubstantial claim - Findingown data§ B cells and tertiary lymphoid structures promote immunotherapy response
Bulk RNA sequencing of melanoma tumours showed that B cell markers were the most differentially expressed genes between immunotherapy responders and non-responders.
“here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders.”
Quote in the paperSubstantial claim - Findingown data
TLSs are associated with B cell proliferation.
“TLSs are associated with markers of T cell activation and response and B cell proliferation.”
Quote in the paperNot a substantial claim - Findingown data
Mass cytometry shows significant differences in B cell populations between responder and non-responder tumours.
“Mass cytometry reveals significant differences in Bcell populations between responder and non-responder tumours.”
Quote in the paperSubstantial claim - Findingown data
Increased numbers of CD20+ B-cell-related exosomes were found in peripheral blood of responders compared with non-responders at early on-treatment time points.
“We also found increased numbers of B-cell-related exosomes (CD20+) in the peripheral blood of responders compared with non-responders at early on-treatment time points”
Quote in the paperNot a substantial claim - Findingown data
CD20+ B cells in TLSs colocalized with CD21+ follicular dendritic cells and MECA79+ high endothelial venules.
“Colocalization with CD21+ follicular dendritic cells and MECA79+ high endothelial venules was also shown”
Quote in the paperNot a substantial claim - Findingown data
In TCGA-SKCM, cases in cluster C had significantly improved overall survival compared with cluster A (P = 0.0068).
“Survival analyses revealed that cases in cluster C had significantly improved overall survival compared with cluster A (P = 0.0068)”
Quote in the paperSubstantial claim - Findingown data
Unbiased marker analysis found 46 markers significantly enriched in responder lesions and 147 markers significantly enriched in non-responder lesions.
“demonstrated 46 markers were significantly enriched in lesions from responders and 147 markers were significantly enriched in non-responder lesions”
Quote in the paperNot a substantial claim - Findingown data
Pathways upregulated in responders versus non-responders included CXCR4 signalling, cytokine receptor interaction, and chemokine signalling pathways.
“Pathways upregulated in responders as compared to non-responders include those consistent with increased immune activity such as CXCR4 signalling, cytokine receptor interaction and chemokine signalling pathways”
Quote in the paperNot a substantial claim - Findingown data
Analysis of TCGA SKCM RNA-seq data with MCP-counter scores identifies three immune classes that differ in presence of individual cell types.
“Unsupervised hierarchical analysis of TCGA SKCM RNA-seq data using MCP-counter scores identifies three MICs with differential presence of individual cell types as indicated.”
Quote in the paperNot a substantial claim - Findingown data
In TCGA-SKCM, patients with B cell-lineage-high tumours had prolonged survival compared with those with B cell-lineage-low tumours (P = 0.053).
“we next compared overall survival in patients with tumours high for B cell lineage versus low, which demonstrated prolonged survival in patients with B cell-lineage-high tumours (P = 0.053)”
Quote in the paperNot a substantial claim - Findingown data
Responders had an increased percentage of CXCR3+ switched memory B cells (P = 0.0083) compared with non-responders.
“More granular characterization of the intratumoral B cells reveals an increased percentage of CXCR3+ switched memory B cells (P = 0.0083) in responders than in non-responders”
Quote in the paperSubstantial claim - Findingown data
Analysis of TCGA KIRC RNA-seq data with MCP-counter scores identifies three immune classes that differ in presence of individual cell types.
“Unsupervised hierarchical analysis of TCGA KIRC RNA-seq data using MCPcounter scores identifies three immune classes with differential presence of individual cell types as indicated.”
Quote in the paperNot a substantial claim - Findingown data
Intratumoral B cells had reduced expression of CD21, CD23, CD79b, and CXCR5 compared with similar B cell populations in peripheral blood.
“Intratumoral B cells had reduced expression of CD21, CD23, CD79b and CXCR5, pointing to distinct functional and migratory profiles compared to similar B cell populations in the peripheral blood”
Quote in the paperNot a substantial claim - Findingown data
Unsupervised k-means clustering identified four distinct B cell clusters (G1-G4) with different functional states.
“identified four distinct B cell clusters, G1 (B cells, switched, activated IgD− cells), G2 (plasma cells), G3 (B cells unswitched IgD+) and G4 (B cells, switched, activated IgD− cells, with unique markers relative to G1), each of which is associated with different functional states”
Quote in the paperNot a substantial claim - Findingown data
Responders had increased germinal-centre-like B cells (P = 0.24) compared with non-responders.
“increased germinal-centre-like (CD19+, CD20++, CD38+, CD27−, IgD−, CD86+, CD95+) B cells (P = 0.24) in responders as compared to non-responders”
Quote in the paperNot a substantial claim - Findingown data
In TCGA-SKCM, univariable Cox modelling showed that tumours with low B cell infiltration had significantly increased risk of death (hazard ratio 1.7, P = 0.05) compared with B-cell-high tumours.
“univariable Cox proportional hazards modelling demonstrated that tumours with low infiltration of B cells had significantly increased risk of death (hazard ratio is 1.7 for B-cell-low, P = 0.05) in comparison to the B-cell-high group”
Quote in the paperSubstantial claim - Findingcitation
The vast majority of evaluated TLSs in these patients were mature secondary-follicle-like TLSs, indicated by the presence of CD21+ follicular dendritic cells and CD23+ germinal centre B cells.
“The vast majority of evaluated TLSs in these patients represented mature secondary-follicle-like TLSs, as indicated by the presence of both CD21+ follicular dendritic cells and CD23+ germinal centre B cells30”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [30] Posch, F. et al. Maturation of tertiary lymphoid structures and recurrence of stage II and III colorectal cancer. OncoImmunology 7, e1378844 (2017). source
Not checked in the free run.
- Findingown data
Responders had increased CD86+ B cells (P = 0.017) compared with non-responders.
“we also note increased CD86+ B cells (P = 0.017)”
Quote in the paperSubstantial claim - Findingown data
In TCGA-SKCM, three distinct melanoma immune classes (MICs) were identified, with significantly higher B cell expression in cluster C than in cluster A or cluster B (P < 0.0001).
“we identified three distinct melanoma immune classes (MICs), with significantly higher expression of B cells in cluster C than in cluster A (P < 0.0001) or cluster B (P < 0.0001)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [42] Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 161, 1681–1696 (2015). source
Not checked in the free run.
- Findingown data
In the TCGA cutaneous melanoma cohort, immune infiltrate predicts improved disease-specific survival.
“Immune infiltrate is prognostic of improved diseasespecific survival in TCGA cutaneous melanoma cohort but not the clear-cell RCC cohort.”
Quote in the paperNot a substantial claim - Findingown data
Single-cell RNA-seq reveals unique B cell clusters associated with response to ICB.
“Single-cell RNA-seq analysis reveals unique clusters of B cells associated with response to ICB.”
Quote in the paperSubstantial claim - Findingown data
In the TCGA clear-cell RCC cohort, immune infiltrate does not predict improved disease-specific survival.
“Immune infiltrate is prognostic of improved diseasespecific survival in TCGA cutaneous melanoma cohort but not the clear-cell RCC cohort.”
Quote in the paperNot a substantial claim - Findingown data
TLSs are associated with markers of T cell activation and response.
“TLSs are associated with markers of T cell activation and response and B cell proliferation.”
Quote in the paperSubstantial claim - Findingown data
Spatial profiling showed increased markers of T cell activation within TLSs compared with outside TLSs.
“found increased markers of activation on T cells within as compared to those outside these TLSs”
Quote in the paperSubstantial claim - Findingown data
Increased proliferation of B cells suggestive of germinal centre formation and activity was observed within TLSs.
“Increased proliferation of B cells suggestive of germinal centre formation and activity is observed within TLSs”
Quote in the paperNot a substantial claim - Findingown data
TLSs show modest correlation with gene expression data.
“TLSs found in nodal and non-nodal metastases are consistent with mature secondary follicular-like TLSs with modest correlation with gene expression data.”
Quote in the paperNot a substantial claim - Findingown data
Peripheral blood B cell subsets (naive, memory, transitional, and plasma cells) had a similar distribution in responders and non-responders.
“Although B cell subsets (naive, memory and transitional B cells and plasma cells) in the peripheral blood had a similar distribution in responders and non-responders”
Quote in the paperNot a substantial claim - Study design and conductown data
The multivariable analyses were limited by low sample size.
“however, these analyses were limited owing to the low sample size”
Quote in the paperSubstantial claim - Interpretationown data
The B cell signature enrichment was not merely due to tumours being located in lymph nodes, because analyses included nodal and extranodal disease with no obvious contribution from disease site.
“Notably, these analyses included samples from patients with nodal and extranodal disease with no obvious contribution based on the site of disease (Fig. 1c, Extended Data Figs. 1a, b, 2a, Supplementary Tables 4, 13), which suggests that B cell signatures were not merely related to the presence of these tumours within lymph nodes.”
Quote in the paperSubstantial claim - Interpretationown data
The BCR findings suggest an active role for B cells in anti-tumour immunity.
“which suggests an active role for B cells in anti-tumour immunity”
Quote in the paperSubstantial claim - Interpretationown data
The same properties of memory B cells and plasma cells desirable for acquired immune responses may also contribute to an effective T cell response after ICB.
“our data suggest that the same properties of memory B cells and plasma cells desirable for acquired immune responses may also be contributing to an effective T cell response after ICB.”
Quote in the paperSubstantial claim - Interpretationown data
Multiomic data support a role for B cells within TLSs in the response to ICB in patients with metastatic melanoma and RCC.
“we present multiomic data that support a role for B cells within TLSs in the response to ICB in patients with metastatic melanoma and RCC.”
Quote in the paperSubstantial claim - Interpretationreasoning
The B cell frequency therefore reflects whether a patient had high or low B cell infiltration.
“the frequency reflects patients with either high or low B cell infiltrate.”
Quote in the paperSubstantial claim - Interpretationreasoning
B cells are probably acting together with other key immune constituents of the TLS by altering T cell activation and function and through other mechanisms.
“Importantly, these B cells are probably acting together with other key immune constituents of the TLS by altering T cell activation and function as well as through other mechanisms.”
Quote in the paperSubstantial claim - Interpretationown data
Memory B cells may act as antigen-presenting cells, driving expansion of memory and naive tumour-associated T cell responses.
“Memory B cells may be acting as antigen-presenting cells, driving the expansion of both memory and naive tumour-associated T cell responses.”
Quote in the paperSubstantial claim - Interpretationown data
TLSs in nodal and non-nodal metastases resemble mature secondary follicular-like TLSs.
“TLSs found in nodal and non-nodal metastases are consistent with mature secondary follicular-like TLSs with modest correlation with gene expression data.”
- Also stated in: § Extended Data · boosted
“Representative TLSs in tumours from patients with melanoma treated with neoadjuvant ICB demonstrating maturation status as indicated by the presence of follicular dendritic cells (CD21) and germinal centre B cells (CD23).”
Quote in the paperNot a substantial claim - Also stated in: § Extended Data · boosted
- May combine two claims. 23
- Classified as probably not a substantial claim. 28
May combine two claims.
Findingown dataIn the neoadjuvant melanoma cohort, B-cell-related genes MZB1, JCHAIN, and IGLL5 were expressed at significantly higher levels in responders than non-responders at baseline (P < 0.001), with over-representation relative to T cells and other immune markers, among seven evaluable responders and nine non-responders.
“significantly higher expression of B-cell-related genes such as MZB1, JCHAIN and IGLL5 was observed in patients that respond to ICB treatment versus non-responding patients (‘responders’ and ‘non-responders’, hereafter) at baseline (P < 0.001) with over-representation of these genes compared to T cells and other immune markers (with evaluable tumours from seven responders and nine non-responders)”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationThe melanoma immune classes had no clear association with known genomic subtypes of melanoma (BRAF, NRAS, NF1, or triple wild type) or with disease site (nodal or non-nodal).
“Importantly, there was no clear association of MICs with known genomic subtypes of melanoma (BRAF, NRAS, NF1 or triple wild type)42 or disease site (nodal or non-nodal)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [42] Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 161, 1681–1696 (2015). source
Not checked in the free run.
May combine two claims.
Findingown dataBulk RNA-seq pathway analysis showed increased immune signalling pathways in responders versus non-responders, including T cell receptor signalling, MHC-mediated antigen presentation and processing, TH1/TH2 differentiation, and costimulatory signalling associated with T cell signalling.
“Pathway analysis was also performed on bulk RNA-seq data from our clinical trial cohort, revealing increased immune signalling pathways in responders than in non-responders, including T cell receptor signalling, major histocompatibility complex-mediated antigen presentation and processing, differentiation of T helper 1 and 2 (TH1 and TH2) cells, and costimulatory signalling associated with T cell”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe CyTOF tumour analysis included 9 responders and 9 non-responders, while the peripheral blood mononuclear cell analysis included 8 responders and 8 non-responders.
“For tumour, this included 9 responders and 9 non-responders, and for peripheral blood mononuclear cells, 8 responders and 8 non-responders.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationIn TCGA-KIRC clear-cell RCC, similar immune classes were observed, but immune infiltration was not associated with survival (P = 0.24).
“Similar analyses were performed to assess the expression of immune-related genes in clear-cell RCC from the TCGA (TCGA-KIRC, n = 526)43. In these analyses, similar immune classes were observed; however, immune infiltration was not associated with survival in these patients (P = 0.24)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [43] Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499, 43–49 (2013). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe final stage III TCGA-SKCM cohort consisted of 136 patients.
“yielding a final stage III TCGA-SKCM cohort of n = 136.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataSingle-cell sequencing produced a median of about 1.4 million paired-end reads and a median of 2,588 detected genes per cell.
“resulting in a median of approximately 1.4 million paired-end reads and a median of 2,588 genes detected per cell.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the neoadjuvant melanoma cohort, CD20+ B cell density, TLS density, and TLS-to-tumour area ratio were higher in responders than non-responders in early on-treatment samples (P = 0.0008, 0.001, and 0.002), but not all markers reached significance at baseline (P = 0.132, 0.078, and 0.037).
“The density of CD20+ B cells and TLSs, and the ratio of TLSs to tumour area were higher in responders than in non-responders in our neoadjuvant melanoma cohort, particularly in early on-treatment samples (P = 0.0008, P = 0.001 and P = 0.002, respectively), although statistical significance was not reached for all the markers in the baseline samples (P = 0.132, P = 0.078 and P = 0.037, respectively”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBCR analysis showed significantly increased clonal counts for IgH and IgL (P = 0.001 and 0.004) and increased BCR diversity in responders versus non-responders (P = 0.002 and 0.0008).
“we identified significantly increased clonal counts for both immunoglobulin heavy and light chains (IgH and IgL; P = 0.001 and P = 0.004, respectively) and increased BCR diversity in responders than in non-responders (P = 0.002 and P = 0.0008)”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataPlasma cells were increased in responders compared with non-responders, but this did not reach significance (P = 0.3) and was largely driven by one patient.
“Other notable differences included an increase in plasma cells in responders compared with non-responders; however, this did not reach significance and was largely driven by data from one patient (P = 0.3)”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAfter excluding cases without expression data, 526 TCGA-KIRC cases were included in subsequent analysis.
“For TCGA-KIRC, the cases without available expression data were excluded and a total of 526 cases were taken into subsequent analysis.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataNo significant associations were found between individual B cell clusters G1-G4 and clinical outcome, probably due to limited sample size.
“No significant differences were identified when testing for associations of each individual cluster (G1–G4) with the clinical outcome, probably owing to limited sample size.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the RCC pre-surgical ICB cohort, increased infiltration of CD20+ cells and TLS density were associated with response to treatment, and these TLSs were morphologically similar to those in melanoma.
“Analogous immunohistochemical findings were observed in our cohort of patients with RCC treated with pre-surgical ICB, with increased infiltration of CD20+ cells and TLSs density associated with response to treatment (Extended Data Fig. 6b–d); these TLSs are morphologically similar to those found in melanoma”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataTLSs are associated with response in RCC, as they are in melanoma.
“TLSs are associated with response in RCC similar to those observed in melanoma.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataTumours from responders had a significantly higher frequency of memory B cells, whereas non-responders had a significantly higher frequency of naive B cells (P = 0.033 for each).
“tumours from responders had a significantly higher frequency of memory B cells, whereas non-responders had a significantly higher frequency of naive B cells (P = 0.033 for naive and P = 0.033 for memory)”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the RCC cohort, B cell signatures predicted response in univariable analysis (odds ratio 61.2, P = 0.05) but not in multivariable analysis.
“As in the case of melanoma, B cell signatures were predictive of a response in univariable analysis in the RCC cohort (odds ratio 61.2, P = 0.05) but not multivariable analysis”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataNine of the 136 TCGA-SKCM samples lacked survival data, leaving 127 samples for overall survival analysis.
“Survival data were missing for 9 of 136 samples, so n = 127 samples were available for overall survival analyses.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn single-cell RNA-seq from an independent metastatic melanoma cohort, B cells were significantly enriched in tumours from responders versus non-responders and were predictive of response (odds ratio 1.05, P = 0.02).
“we found that B cells were significantly enriched in tumours from responders versus non-responders and were predictive of a response (odds ratio 1.05, P = 0.02)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [44] Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013 (2018). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe selected unsupervised clustering solution used k=11 and had a median robustness score of 0.96.
“This process yielded a median robustness measure of 0.96 for the selected k=11.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataTwenty-eight pre-treatment RCC samples were available across three arms: nivolumab (6), nivolumab plus bevacizumab (14), and nivolumab plus ipilimumab (8).
“There are 28 available pre-treatment samples from 3 arms: nivolumab (n = 6), nivolumab plus bevacizumab (n = 14) and nivolumab plus ipilimumab (n = 8).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataCD20+ B cells were localized in TLSs of tumours from responders and colocalized with CD4+, CD8+, and FOXP3+ T cells.
“architectural analysis showed that CD20+ B cells were localized in TLSs of tumours of responders, and were colocalized with CD4+, CD8+and FOXP3+ T cells.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataB cells probably act together with other immune subsets and are not acting in isolation.
“which suggests that B cells probably act together with other immune subsets and are not acting in isolation”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationB cells have previously been shown to be positively associated with responses to chemotherapy in other cancer types.
“however, B cells have previously been shown to be positively associated with responses to chemotherapy in other cancer types39,40.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [39] Reddy, S. M. et al. Poor response to neoadjuvant chemotherapy correlates with mast cell infiltration in inflammatory breast cancer. Cancer Immunol. Res. 7, 1025–1035 (2019). source
Not checked in the free run.
- cites [40] Song, I. H. et al. Predictive value of tertiary lymphoid structures assessed by high endothelial venule counts in the neoadjuvant setting of triple-negative breast cancer. Cancer Res. Treat. 49, 399–407 (2017). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe RCC multivariable analysis was limited by sample size.
“however, sample size was again limited”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe study did not use statistical methods to predetermine sample size.
“No statistical methods were used to predetermine sample size.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataAfter reviewing a Spearman correlation matrix, a sequencing event from one library pool that correlated poorly with other pools from the same RNA sample was excluded before BAM files were merged at the sample level.
“The correlation matrix was carefully reviewed and the sequencing event generated from one library pool that showed poor correlation with other library pools from the same RNA sample were removed before sample-level merging of BAM files.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenSamples containing fewer than 200 CD45+CD19+ B cells were excluded from downstream analyses.
“Samples with fewer than 200 CD45+CD19+ B cells were not used for downstream analyses.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningSwitched memory B cells observed in responders could potentially contribute to anti-tumour response by producing antibodies against tumours.
“The observation of switched memory B cells (that can differentiate into plasma cells) in responders suggests that they could be potentially contributing to the anti-tumour response by producing antibodies against the tumours.”
Quote in the paperNot a substantial claim- Rests on an assumption: Switched memory B cells can differentiate into plasma cells.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataTransmission electron micrographs showed Dynabeads with exosomes present after immunocapture.
“Representative transmission electron micrographs showing Dynabead with exosomes present after immunocapture.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductown dataFor each patient, the same number of CD45+ cells (384 per plate) was collected and sequenced, making the cell count per patient equal.
“for each patient, we collected and sequenced the same number of cells (n = 384 CD45+ cells per plate). Thus, the number of cells per patient is equal”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenRNA integrity was evaluated with an Agilent 2100 Bioanalyzer and RNA 6000 Nano Chip, using smear analysis to measure DV200 and initial RNA concentration.
“RNA quality was assessed on an Agilent 2100 Bioanalyzer using the Agilent RNA 6000 Nano Chip with smear analysis to determine DV200 and original RNA concentration.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningTechnical replicates were limited to one per time point because of limited patient-derived tissue and prioritization for other studies.
“Technical replicates were constrained to n = 1 per time point, owing to limited tissue availability in patient-derived samples as well as prioritization for multiple studies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataNanoimager images showed beads coated with CD63+ exosomes compared with isotype control.
“Nanoimager-captured images of the beads coated with CD63+ exosomes as compared with isotype control.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenProtein targets with a signal-to-noise ratio below 2 were excluded from downstream analysis.
“Protein targets with a signal to noise ratio less than 2 were removed from downstream analysis.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenFor multiplex immunofluorescence, five random areas per sample were evaluated blindly by a pathologist at 20× magnification.
“Five random areas on each sample were analysed blindly by a pathologist at 20× magnification.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenOnly in-frame productive BCR clonotypes were retained for subsequent analysis.
“Only in-frame productive clonotypes were taken into subsequent analysis.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataRunning tumour and peripheral blood samples from melanoma patients treated with ICB together in mass cytometry eliminated batch effect.
“These data represent combined tumour and peripheral blood samples from patients with melanoma treated with ICB ran together (8 tumour n = 5 R and n = 3 NR and 8 peripheral blood samples n = 4 R and n = 4 NR), thus eliminating batch effect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe experiments were not randomized.
“The experiments were not randomized”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataOne exosome sample had an erroneous Nanosight measurement and was excluded from that measurement, but all samples were included in flow cytometric analyses.
“For one sample, the Nanosight measurement was erroneous and excluded. All samples were included in the flow cytometric analyses.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenSequencing reads containing at least 15 consecutive low-quality bases (phred score below 20) were filtered out of the FASTQ files.
“The reads that had ≥ 15 contiguous low-quality bases (phred score < 20) were removed from the FASTQ files.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenInvestigators were not blinded to allocation during experiments or outcome assessment unless otherwise stated.
“investigators were not blinded to allocation during experiments and outcome assessment unless stated otherwise.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataSimilar mature TLSs were identified in patients with extra-nodal metastases, suggesting that TLSs may develop in non-nodal sites and are associated with response to ICB treatment.
“We identify similar mature TLSs in patients with extra-nodal metastases (Extended Data Fig. 5b), which suggests that TLSs may develop in non-nodal sites and are associated with the response to ICB treatment.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenResponder versus non-responder status remained blinded until flow cytometry data capture and FlowJo analyses were finished.
“Responder versus non-responder status was blinded until flow cytometry data capture and FlowJo analyses were completed.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
B cells can secrete cytokines including TNF, IL-2, IL-6, and IFNγ, and through these cytokines activate and recruit other immune effector cells including T cells.
“B cells can also secrete an array of cytokines (including TNF, IL-2, IL-6 and IFNγ), through which they activate and recruit other immune effector cells, including T cells.”
The paper relies on this without support.
Switched memory B cells can differentiate into plasma cells.
“switched memory B cells (that can differentiate into plasma cells)”
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?
Tumor-associated tertiary lymphoid structures are emerging as a powerful prognostic marker in melanoma and a number of other cancer types.
“Also, as a member of the 12-chemokine gene signature classifier33, its expression has been correlated with the presence of tumor-associated tertiary lymphoid structures50–52 which are rapidly emerging as a powerful prognostic marker in melanoma and a number of other cancer types53–55.”
From Epigenetic state determines the in vivo efficacy of STING agonist therapy (2023) · cites this paper as [54]
The section “B cells prognostic in TCGA analysis” describes existing evidence for a potential prognostic role for TLSs in melanoma and other cancer types. It also reports improved survival for a melanoma group with higher B-cell expression, but that is not a direct measure of TLSs. The source therefore supports the emerging prognostic association, not the stronger description of TLSs as a powerful prognostic marker across those cancers. (LLM, conf=0.83)
Experimental — accuracy not yet measuredTertiary lymphoid structures have emerged as biomarkers of response to immune checkpoint therapy across several tumor types including lung cancer, melanoma, RCC, sarcoma, and urothelial cancer.
“Tertiary lymphoid structures (TLS) have recently emerged as biomarkers of response to ICT across several tumor types, including lung cancer, melanoma, RCC, sarcoma, and urothelial cancer (163-167).”
From The Next Decade of Immune Checkpoint Therapy (2021) · cites this paper as [164]
Presence of B cells in tumor is associated with better response to neoadjuvant ICB in melanoma and renal cell carcinoma.
“Presence of B cells in tumor was associated with a better response to neoadjuvant therapy with ICB in melanoma and renal cell carcinoma (Cabrita et al., 2020; Helmink et al., 2020).”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Helmink et al., 2020
Tumor-infiltrating B cell populations in responder tumors are enriched in memory B cells, while naïve B cells are more prominent in non-responder tumors.
“Tumor-infiltrating B cell populations in responder tumors were enriched in memory B cells; in contrast, naïve B cells were more prominent in non-responder tumors (Helmink et al., 2020).”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Helmink et al., 2020
Evidence supports a role for the gut and tumor microbiome, stress, and diet in tumor immunity and in response to immune checkpoint blockade.
“Mounting evidence on the role of the gut and tumor microbiome, stress, and diet in tumor immunity and response to ICB (Helmink et al., 2020) has created a foundation for emerging adjunct therapies.”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Helmink et al., 2020
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.
Survival endpoint differs between the figure title and description
MinorThe figure title identifies disease-specific survival as the endpoint, but the figure description and Methods identify overall survival. These are different endpoints.
“Figure: Extended Data Fig. 4 | Immune infiltrate is prognostic of improved diseasespecific survival in TCGA cutaneous melanoma cohort but not the clear-cell RCC cohort.”
“b, Kaplan–Meier estimates of overall survival of MIC groups. c, Kaplan–Meier estimates of overall survival by B cell lineage scores shown by high and low groups dichotomized by median values.”
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Self-citationDefining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma
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Self-citationNeoadjuvant immune checkpoint blockade in high-risk resectable melanoma
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Maturation of tertiary lymphoid structures and recurrence of stage II and III colorectal cancer
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B cells sustain inflammation and predict response to immune checkpoint blockade in human melanoma
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The Emerging Role of B Cells in Tumor Immunity
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Self-citationHigh endothelial venules (HEVs) in human melanoma lesions
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Landscape of B cell immunity and related immune evasion in human cancers
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“The modified TRUST algorithm 56 was applied to extract the B-cell immunoglobin hypervariable regions from the bulk RNA-seq data and assembly the complementarity-determining region 3”
Self-citationSpecies identity of insect cell lines
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PD-L1 and Emerging Biomarkers in Immune Checkpoint Blockade Therapy
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Tumor-associated B cells in cutaneous primary melanoma and improved clinical outcome
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Self-citationPrognostic value of B cells in cutaneous melanoma
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“…understood 14,15,19-24 – with some studies suggesting that they are tumor-promoting while others show a positive association with improved cancer outcomes, particularly when they are found in association with organized lymphoid aggregates known as tertiary lymphoid structures (TLS) 12,13,16,25-27 .”
B cells sustain inflammation and predict response to immune checkpoint blockade in human melanomaPreprint
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Energy transfer to the triplet level of all-trans retinal
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Zhang, Y., & Zhang, Z. (2020) · Cellular and Molecular Immunology · doi:10.1038/s41423-020-0488-6 · Cited by 2,815 · see citing works
Tertiary lymphoid structures improve immunotherapy and survival in melanoma
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Self-citationB cells are associated with survival and immunotherapy response in sarcoma
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Self-citationHallmarks of response, resistance, and toxicity to immune checkpoint blockade
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Self-citationThe immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy
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Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers
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“This finding is in accordance with studies demonstrating that tumor-infiltrating and systemic B cell responses are both predictive and indicative of responses to immunotherapy (Helmink et al., 2020).”
ResultTertiary lymphoid structures in cancer
Schumacher, T. N., & Thommen, D. S. (2022) · Science · doi:10.1126/science.abf9419 · Cited by 1,147 · see citing works
“Although a number of observations are consistentwith a model in which ICB affects TLS functionality (15, 136, 137), the evidence is still circumstantial.”
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CD8+ T cell differentiation and dysfunction in cancer
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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
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“The selective expression of CCR5 and CXCL13 in neoantigen-specific T cells further suggests that a key feature of CPI-responsiveness is the ability to sustain ongoing priming and recruitment of tumour reactive T cells supported by CXCR5+ lymphocytes, which may include T and B cells (Helmink et al., 2020).”
Spatially organized multicellular immune hubs in human colorectal cancer
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“, 2016), contain germinal center B cells, and have been associated with high T cell activity, favorable prognosis, and effective response to immunotherapy (Cabrita et al., 2020; Coppola et al., 2011; Helmink et al., 2020; Petitprez et al., 2020; Sautès-Fridman et al., 2019).”
BackgroundSelf-citationTumor-infiltrating lymphocytes in the immunotherapy era
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“Increased BCR diversity and clonal expansion were also observed in tumors of melanoma patients.(75) Of note, some autoantibodies have also been found to be tumor promoting.”
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A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer
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The Next Decade of Immune Checkpoint Therapy
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The Lymphatic Vasculature in the 21st Century: Novel Functional Roles in Homeostasis and Disease
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Self-citationB cells, plasma cells and antibody repertoires in the tumour microenvironment
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The Tumor Microenvironment in the Response to Immune Checkpoint Blockade Therapies
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Self-citationMicrobiota triggers STING-type I IFN-dependent monocyte reprogramming of the tumor microenvironment
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Tumour-infiltrating B cells: immunological mechanisms, clinical impact and therapeutic opportunities
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Spatial profiling technologies illuminate the tumor microenvironment
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Targeting the gut and tumor microbiota in cancer
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Self-citationIntratumoural administration and tumour tissue targeting of cancer immunotherapies
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“Tertiary lymphoid structures (TLSs) are ectopic hyperplasia lymphoid tissues located outside the immune organs (85) that are present in a fraction of specific types of tumors.”
MethodInfluentialAndersson, A., Larsson, L., Stenbeck, L., Salmén, F., Ehinger, A., Wu, S. Z., Al-Eryani, G., Roden, D., Swarbrick, A., Borg, Å., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26271-2 · Cited by 404 · see citing works
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Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer
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Enhancing anti-tumour efficacy with immunotherapy combinations
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“, 2018), but they also need to analyze the composition of the immune infiltrate and its expression of immune activating gene programs (Auslander et al., 2018; Ayers et al., 2017; Cabrita et al., 2020; Chen et al., 2016; Cristescu et al., 2018; Fehrenbacher et al., 2016; Gide et al., 2019; Helmink et al., 2020; Jerby-A…”
BackgroundResultSTING Agonists as Cancer Therapeutics
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ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis
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Targeting LAG-3, TIM-3, and TIGIT for cancer immunotherapy
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“Mechanistically, the chemokine CXCL13 in the TME may play a crucial role as a B cell attractant [192].”
BackgroundAn ex vivo tumor fragment platform to dissect response to PD-1 blockade in cancer
Voabil, P., de Bruijn, M., Roelofsen, L. M., Hendriks, S. H., Brokamp, S., van den Braber, M., Broeks, A., Sanders, J., Herzig, P., Zippelius, A., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01398-3 · Cited by 380 · see citing works
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“Other studies have indicated that the formation of tertiary lymphoid structures (TLS), which are aggregations of B cells, T cells, dendritic cells (DC), and high endothelial venules, promote immunotherapy response [13].”
BackgroundResultInsights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment
Ren, X., Zhang, L., Zhang, Y., Li, Z., Siemers, N. O., & Zhang, Z. (2021) · Annual Review of Immunology · doi:10.1146/annurev-immunol-110519-071134 · Cited by 369 · see citing works
Towards targeting the breast cancer immune microenvironment
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“…TLSs in breast cancer TME are not yet clear, neither are there internationally accepted criteria on how to define or quantify TLSs using histopathological slides; however, studies in renal cell carcinoma and melanoma have found both TLSs and B cells are associated with good responses to ICB 60 .”
Ho, W. J., Zhu, Q., Durham, J., Popovic, A., Xavier, S., Leatherman, J., Mohan, A., Mo, G., Zhang, S., Gross, N., et al. (2021) · Nature Cancer · doi:10.1038/s43018-021-00234-4 · Cited by 360 · see citing works
Self-citationDissecting Esophageal Squamous-Cell Carcinoma Ecosystem by Single-Cell Transcriptomic Analysis
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“Because B cells are critical for tertiary lymphoid structures (TLS), a tumor infiltrated ectopic lymphoid organ similar to SLOs, multiple studies found the higher number of infiltrating B cells in TLS indicate a better patient survival with malignant tumors, however the mechanism remains unclear [168, 169].”
Role of B cells as antigen presenting cells
Rastogi, I., Jeon, D., Moseman, J. E., Muralidhar, A., Potluri, H. K., & McNeel, D. G. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.954936 · Cited by 352 · see citing works
“Several groups have also shown that the presence of TLS is associated with response to immune checkpoint blockade (11, 13, 14).”
BackgroundMoving towards personalized treatments of immune-related adverse events
Esfahani, K., Elkrief, A., Calabrese, C., Lapointe, R., Hudson, M., Routy, B., Miller, W. H., & Calabrese, L. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-0352-8 · Cited by 351 · see citing works
STING-induced regulatory B cells compromise NK function in cancer immunity
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Neoadjuvant relatlimab and nivolumab in resectable melanoma
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Self-citationTreatment of Advanced Melanoma in 2020 and Beyond
Jenkins, R. W., & Fisher, D. E. (2020) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2020.03.943 · Cited by 343 · see citing works
Principles and therapeutic applications of adaptive immunity
Chi, H., Pepper, M., & Thomas, P. G. (2024) · Cell · doi:10.1016/j.cell.2024.03.037 · Cited by 359 · see citing works
Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations
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Self-citationLymph node stromal cells: cartographers of the immune system
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Tertiary lymphoid structures and B cells: An intratumoral immunity cycle
Fridman, W. H., Meylan, M., Pupier, G., Calvez, A., Hernández-Verdín, I., & Sautès‐Fridman, C. (2023) · Immunity · doi:10.1016/j.immuni.2023.08.009 · Cited by 331 · see citing works
Self-citationThe roles of tertiary lymphoid structures in chronic diseases
Sato, Y., Siliņa, K., van den Broek, M. F., Hirahara, K., & Yanagita, M. (2023) · Nature Reviews Nephrology · doi:10.1038/s41581-023-00706-z · Cited by 328 · see citing works
“A single-cell RNA sequencing analysis of B cells derived from human tumours identified unswitched IgD + B cells, switched IgG + B cells and a wide range of B cells that expressed genes that are associated with immature or mature germinal centres 11,12 .”
InfluentialGao, J., Navai, N., Alhalabi, O., Siefker-Radtke, A., Campbell, M. T., Tidwell, R. S., Guo, C. C., Kamat, A. M., Matin, S. F., Araujo, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1086-y · Cited by 318 · see citing works
Self-citationOveracre-Delgoffe, A. E., Bumgarner, H. J., Cillo, A. R., Burr, A. H. P., Tometich, J. T., Bhattacharjee, A., Bruno, T. C., Vignali, D. A. A., & Hand, T. W. (2021) · Immunity · doi:10.1016/j.immuni.2021.11.003 · Cited by 318 · see citing works
Monocytes in the Tumor Microenvironment
Ugel, S., Canè, S., Sanctis, F. D., & Bronte, V. (2021) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012418-013058 · Cited by 316 · see citing works
Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment
Polak, R., Zhang, E., & Kuo, C. J. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00706-6 · Cited by 322 · see citing works
“Studying patient-derived tissue sections of ICB responders and non-responders, single-cell RNA sequencing has been combined with mass cytometry to define the potential role of B cells and TLSs during ICB 14 .”
Improving head and neck cancer therapies by immunomodulation of the tumour microenvironment
Ruffin, A., Li, H., Vujanović, L., Zandberg, D., Ferris, R., & Bruno, T. (2022) · Nature Reviews. Cancer · doi:10.1038/s41568-022-00531-9 · Cited by 293 · see citing works
Rivellese, F., Surace, A. E. A., Goldmann, K., Sciacca, E., Çubuk, C., Giorli, G., John, C. R., Nerviani, A., Fossati‐Jimack, L., Thorborn, G., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01789-0 · Cited by 302 · see citing works
Self-citationDefining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours
Holder, A. M., Dedeilia, A., Sierra-Davidson, K., Cohen, S., Liu, D., Parikh, A. R., & Boland, G. M. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00705-7 · Cited by 313 · see citing works
Tertiary lymphoid structures in anticancer immunity
Teillaud, J., Houel, A., Panouillot, M., Riffard, C., & Dieu‐Nosjean, M. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00728-0 · Cited by 303 · see citing works
“Moreover, this predictive status is specifically linked to B cells of TLS in several types of solid tumour 25,105,106,157 .”
InfluentialImmune-related toxicities of checkpoint inhibitors: mechanisms and mitigation strategies
Sullivan, R. J., & Weber, J. S. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00259-5 · Cited by 303 · see citing works
Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer
Lin, J., Wang, S., Coy, S., Chen, Y., Yapp, C., Tyler, M., Nariya, M. K., Heiser, C. N., Lau, K. S., Santagata, S., et al. (2023) · Cell · doi:10.1016/j.cell.2022.12.028 · Cited by 284 · see citing works
“50,51 Pathology inspection of 47 individual sections of CRC1 (22 H&E and 25 CyCIF) identified over 900 distinct SLO and TLS domains in2D (Figures 6A and S5A).”
BackgroundApplying high-dimensional single-cell technologies to the analysis of cancer immunotherapy
Gohil, S. H., Iorgulescu, J. B., Braun, D. A., Keskin, D. B., & Livak, K. J. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-00449-x · Cited by 282 · see citing works
How chemokines organize the tumour microenvironment
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B Cell Function in the Tumor Microenvironment
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“Especially those B cells located in mature TLS may exhibit immunostimulatory functions by closely interacting with local T cells, thereby enhancing anti-cancer immunity.”
BackgroundResultInfluentialRelevance of immune cell and tumor microenvironment imaging in the new era of immunotherapy
Galli, F., Aguilera, J. V., Palermo, B., Markovic, S. N., Nisticò, P., & Signore, A. (2020) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-020-01586-y · Cited by 281 · see citing works
“From the clinical point of view, it is urgent to understand whether the presence and localization of TLS in pretreatment or longitudinal tumor tissue samples during and post-treatment, may be validated as prognostic/ predictive of responses to checkpoint blockade, with far reaching clinical implications, as recently r…”
BackgroundBreast tumor microenvironment structures are associated with genomic features and clinical outcome
Danenberg, E., Bardwell, H. A., Zanotelli, V. R., Provenzano, E., Chin, S., Rueda, O. M., Green, A. R., Rakha, E. A., Aparicio, S. A. J. R., Ellis, I. O., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01041-y · Cited by 273 · see citing works
“By contrast, TME cell diversity differed markedly: There was higher diversity among ER-negative subtypes (Basal; IntClusts 4, 5, and 10) and lesser diversity among indolent ER-positive subtypes (Luminal A; IntClusts 3 and 8).”
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“Recent publications reported that TA-TLS presence prior to treatment was associated with a favorable response to immunotherapy in patients with cancer (Griss et al., 2019; Cabrita et al., 2020; Petitprez et al., 2020; Helmink et al., 2020).”
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“277 Collectively, these studies indicate that the mouse and human gut microbiota may play a crucial role in regulating tumor IVDR on ICIs by modulating the host immune system.”
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“Importantly, we found that the detected immune cell region resembles a tertiary lymphoid structure (TLS) 60,61 with multiple features of TLS: the region is located near the tumor; the region primarily contains T cells and B cells, all of which are key cell types in TLS 60,62 – 64 ; the region is…”
BackgroundPre-metastatic niche: formation, characteristics and therapeutic implication
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“91,92 Conversely, under particular circumstances, such as regulatory B cells and regulatory T cells (Tregs), T and B cells can also act in an immunosuppressive capacity.”
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IgA transcytosis and antigen recognition govern ovarian cancer immunity
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“Understanding the different interactions that occur within the TLSs, as well as the mechanism of TLS formation, may suggest ways to induce TLS formation in non-immunogenic tumours.”
BackgroundInfluentialSelf-citationUnraveling B cell trajectories at single cell resolution
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- Authors
- Helmink, B. A., Reddy, S. M., Gao, J., Zhang, S., Basar, R., Thakur, R., Yizhak, K., Sade-Feldman, M., Blando, J., Han, G., Gopalakrishnan, V., Xi, Y., Zhao, H., Amaria, R. N., Tawbi, H. A., Cogdill, A. P., Liu, W., LeBleu, V. S., Kugeratski, F. G., Patel, S., Davies, M. A., Hwu, P., Lee, J. E., Gershenwald, J. E., Lucci, A., Arora, R., Woodman, S., Keung, E. Z., Gaudreau, P.-O., Reuben, A., Spencer, C. N., Burton, E. M., Haydu, L. E., Lazar, A. J., Zapassodi, R., Hudgens, C. W., Ledesma, D. A., Ong, S., Bailey, M., Warren, S., Rao, D., Krijgsman, O., Rozeman, E. A., Peeper, D., Blank, C. U., Schumacher, T. N., Butterfield, L. H., Zelazowska, M. A., McBride, K. M., Kalluri, R., Allison, J., Petitprez, F., Fridman, W. H., Sautès-Fridman, C., Hacohen, N., Rezvani, K., Sharma, P., Tetzlaff, M. T., Wang, L., & Wargo, J. A.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Massachusetts General Hospital (US)
- Broad Institute (US)
- Parker Institute for Cancer Immunotherapy (US)
- Nanostring Technologies (United States) (US)
- The Netherlands Cancer Institute (NL)
- University of Pittsburgh (US)
- Inserm (FR)
- Corresponding author
- Helmink, Beth A.
- Wargo, Jennifer A.
- ORCID
- Helmink, Beth A.
- Reddy, Sangeetha M.
- Gao, Jianjun
- Zhang, Shaojun
- Thakur, Rohit
- Yizhak, Keren
- Sade-Feldman, Moshe
- Blando, Jorge
- Han, Guangchun
- Gopalakrishnan, Vancheswaran
- Xi, Yuanxin
- Zhao, Hao
- Liu, Wenbin
- LeBleu, Valerie S.
- Kugeratski, Fernanda G.
- Patel, Sapna
- Davies, Michael A.
- Hwu, Patrick
- Lee, Jeffrey E.
- Gershenwald, Jeffrey E.
- Lucci, Anthony
- Arora, Reetakshi
- Woodman, Scott
- Keung, Emily Z.
- Gaudreau, Pierre-Olivier
- Reuben, Alexandre
- Spencer, Christine N.
- Burton, Elizabeth M.
- Haydu, Lauren E.
- Lazar, Alexander J.
- Hudgens, Courtney W.
- Rao, Disha
- Krijgsman, Oscar
- Rozeman, Elisa A.
- Peeper, Daniel
- Blank, Christian U.
- Schumacher, Ton N.
- Zelazowska, Monika A.
- McBride, Kevin M.
- Kalluri, Raghu
- Allison, James
- Petitprez, Florent
- Fridman, Wolf Herman
- Hacohen, Nir
- Rezvani, Katayoun
- Sharma, Padmanee
- Wang, Linghua
- Wargo, Jennifer A.
- Venue
- Nature
- Published
- 2020-01-15
- Volume
- 577
- Issue
- 7791
- Pages
- 549-555
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC8762581
- OpenAlex
- W2998795792
- Cited by
- 2,731
- References
- 66
- Citations by year
- 2026: 422 · 2025: 422 · 2024: 458 · 2023: 393 · 2022: 433 · 2021: 383 · 2020: 217
- FWCI
- 129.90
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
- AIM at Melanoma
- Parker Institute for Cancer Immunotherapy
- National Institutes of Health (W81XWH, CA- 016672)
- University of Texas MD Anderson Cancer Center ((CA016672), T32 CA 009599, P30-CA-016672)
- National Cancer Institute (T32CA009666, R01CA213233, CA213233, R01CA195733, CA195733, P30CA008748, T32CA009599, P30CA016672, P01CA117969)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- B cells, tertiary lymphoid structures, immune checkpoint blockade, cancer immunotherapy response, melanoma, renal cell carcinoma, switched memory B cells, B cell clonal expansion, tumor immune microenvironment, predictive biomarkers, MCP-counter, tumor-infiltrating immune cells
- MeSH terms
- Tertiary Lymphoid Structures, RNA-Seq, B-Lymphocytes, Carcinoma, Renal Cell, Clone Cells, Humans, Immunologic Memory, Immunotherapy, Melanoma, Neoplasm Metastasis, Phenotype, Prognosis, Receptors, Immunologic, Mass Spectrometry, T-Lymphocytes, Biomarkers, Tumor, Gene Expression Regulation, Neoplastic, Dendritic Cells, Follicular, Single-Cell Analysis, Cell Cycle Checkpoints, Transcriptome
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