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Early B cell changes predict autoimmunity following combination immune checkpoint blockade.

ABSTRACT: Combination checkpoint blockade (CCB) targeting inhibitory CTLA4 and PD1 receptors holds promise for cancer therapy. Immune-related adverse events (IRAEs) remain a major obstacle for the optimal application of CCB in cancer. Here, we analyzed B cell changes in patients with melanoma following treatment with either anti-CTLA4 or anti-PD1, or in combination. CCB therapy led to changes in circulating B cells that were detectable after the first cycle of therapy and characterized by a decline in circulating B cells and an increase in CD21lo B cells and plasmablasts. PD1 expression was higher in the CD21lo B cells, and B cell receptor sequencing of these cells demonstrated greater clonality and a higher frequency of clones compared with CD21hi cells. CCB induced proliferation in the CD21lo compartment, and single-cell RNA sequencing identified B cell activation in cells with genomic profiles of CD21lo B cells in vivo. Increased clonality of circulating B cells following CCB occurred in some patients. Treatment-induced changes in B cells preceded and correlated with both the frequency and timing of IRAEs. Patients with early B cell changes experienced higher rates of grade 3 or higher IRAEs 6 months after CCB. Thus, early changes in B cells following CCB may identify patients who are at increased risk of IRAEs, and preemptive strategies targeting B cells may reduce toxicities in these patients.

SUBMITTER: Das R

PROVIDER: S-EPMC5785243 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Early B cell changes predict autoimmunity following combination immune checkpoint blockade.

Das Rituparna R Bar Noffar N Ferreira Michelle M Newman Aaron M AM Zhang Lin L Bailur Jithendra Kini JK Bacchiocchi Antonella A Kluger Harriet H Wei Wei W Halaban Ruth R Sznol Mario M Dhodapkar Madhav V MV Dhodapkar Kavita M KM

The Journal of clinical investigation 20180108 2

Combination checkpoint blockade (CCB) targeting inhibitory CTLA4 and PD1 receptors holds promise for cancer therapy. Immune-related adverse events (IRAEs) remain a major obstacle for the optimal application of CCB in cancer. Here, we analyzed B cell changes in patients with melanoma following treatment with either anti-CTLA4 or anti-PD1, or in combination. CCB therapy led to changes in circulating B cells that were detectable after the first cycle of therapy and characterized by a decline in cir ...[more]

PMID: 29309048

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Project description:Immune checkpoint blockade (ICB) is the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), yet efficacy remains low. The current approach for predicting the likelihood of response to ICB is a single proportional biomarker (PD-L1) expressed in immune and tumor cells (Combined Positive Score, CPS) without differentiation by cell type, potentially explaining its limited predictive value. Tertiary Lymphoid Structures (TLS) have shown a stronger association with ICB response than PD-L1. However, their exact composition, size, and spatial biology in HNSCC remain understudied. A detailed understanding of TLS is required for future use as a clinically applicable predictive biomarker.MethodsPre-ICB tumor tissue sections were obtained from 9 responders (complete response, partial response, or stable disease) and 11 non-responders (progressive disease) classified via RECISTv1.1. A custom multi-immunofluorescence (mIF) staining assay was designed, optimized, and applied to characterize tumor cells (pan-cytokeratin), T cells (CD4, CD8), B cells (CD19, CD20), myeloid cells (CD16, CD56, CD163), dendritic cells (LAMP3), fibroblasts (α Smooth Muscle Actin), proliferative status (Ki67) and immunoregulatory molecules (PD1). Spatial metrics were compared among groups. Serial tissue sections were scored for TLS in both H&E and mIF slides. A machine learning model was employed to measure the effect of these metrics on achieving a response to ICB (SD, PR, or CR).ResultsA higher density of B lymphocytes (CD20+) was found in responders compared to non-responders to ICB (p=0.022). A positive correlation was observed between mIF and pathologist identification of TLS (R 2 = 0.66, p-value= <0.0001). TLS trended toward being more prevalent in responders to ICB (p=0.0906). The presence of TLS within 100 μm of the tumor was associated with improved overall (p=0.04) and progression-free survival (p=0.03). A multivariate machine learning model identified TLS density as a leading predictor of response to ICB with 80% accuracy.ConclusionImmune cell densities and TLS spatial location within the tumor microenvironment play a critical role in the immune response to HNSCC and may potentially outperform CPS as a predictor of ICB response.

Project description:In advanced cancer patients undergoing immune checkpoint blockade, the burden of immune-related adverse events (irAEs) is high. The need for reliable biomarkers for irAEs remains unfulfilled in this expanding therapeutic field. The lung immune prognostic index (LIPI) is a noninvasive measure of systemic inflammation that has consistently shown a correlation with survival in various cancer types when assessed at baseline. This study sought to determine whether early changes in the LIPI score could discriminate the risk of irAEs and different survival outcomes in advanced non-small cell lung cancer (NSCLC) patients receiving PD-(L)1 blockade-based therapies. We included consecutive patients diagnosed with metastatic NSCLC who received pembrolizumab, nivolumab, or atezolizumab as second-line therapy following platinum-based chemotherapy, or first-line pembrolizumab either alone or in combination with platinum-based chemotherapy. The LIPI score relied on the combined values of derived neutrophil/lymphocyte ratio (dNLR) and lactate dehydrogenase. Their assessment at baseline and after two cycles of treatment allowed us to categorize the population into three subgroups with good (LIPI-0), intermediate (LIPI-1), and poor (LIPI-2) prognosis. Between April 2016 and May 2023, we enrolled a total of 345 eligible patients, 165 (47.8%) and 180 (52.2%) of whom were treated as first- and second-line at our facility, respectively. After applying propensity score matching, we considered 83 relevant patients in each cohort with a homogeneous distribution of all characteristics across the baseline LIPI subgroups. There was a noticeable change in the distribution of LIPI categories due to a significant decrease in dNLR values during treatment. Although no patients shifted to a worse prognosis category, 20 (24.1%) transitioned from LIPI-1 to LIPI-0, and 7 (8.4%) moved from LIPI-2 to LIPI-1 (p < 0.001). Throughout a median observation period of 7.3 (IQR 3.9-15.1) months, a total of 158 irAEs (63.5%) were documented, with 121 (48.6%) and 39 (15.7%) patients experiencing mild to moderate and severe adverse events, respectively. Multivariate logistic regression analysis showed that the classification and changes in the LIPI score while on treatment were independent predictors of irAEs. The LIPI-0 group was found to have significantly increased odds of experiencing irAEs. Following a median follow-up period of 21.1 (95% CI 17.9-25.8) months, the multivariable Cox model confirmed LIPI categorization at any given time point as a significant covariate with influence on overall survival, irrespective of the treatment line. These findings suggest that reassessing the LIPI score after two cycles of treatment could help pinpoint patients particularly prone to immune-related toxicities. Those who maintain a good LIPI score or move from the intermediate to good category would be more likely to develop irAEs. The continuous assessment of LIPI provides prognostic insights and could be useful for predicting the benefit of PD-(L)1 checkpoint inhibitors.

Dataset Information

Early B cell changes predict autoimmunity following combination immune checkpoint blockade.

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Early B cell changes predict autoimmunity following combination immune checkpoint blockade.

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