Predicting anti-PD-1 responders in malignant melanoma from the frequency of S100A9+ monocytes in the blood

Prospective associations of leucocyte subtypes and obesity with the risk of developing cutaneous malignant melanoma in the UK Biobank cohort

BACKGROUND

Obesity is associated with chronic low-grade inflammation, which is linked to cancer development. Abdominal obesity (a body mass index, ABSI), however, has unusually been associated inversely with cutaneous malignant melanoma (CMM), while general obesity (body mass index, BMI) is associated positively. Leucocytes participate in inflammation and are higher in obesity, but prospective associations of leucocytes with cutaneous malignant melanoma are unclear.

METHODS

We examined the prospective associations of neutrophil, lymphocyte, and monocyte counts (each individually), as well as the prospective associations of ABSI and BMI, with cutaneous malignant melanoma in UK Biobank. We used multivariable Cox proportional hazards models and explored heterogeneity according to sex, menopausal status, age (≥ 50 years at recruitment), smoking status, ABSI (dichotomised at the median: ≥73.5 women; ≥79.8 men), BMI (normal weight, overweight, obese), and time to diagnosis.

RESULTS

During a mean follow-up of 10.2 years, 2174 CMM cases were ascertained in 398,450 participants. There was little evidence for associations with neutrophil or lymphocyte counts. Monocyte count, however, was associated inversely in participants overall (HR = 0.928; 95%CI: 0.888-0.971; per one standard deviation increase; SD = 0.144*109/L women; SD = 0.169*109/L men), specifically in older participants (HR = 0.906; 95%CI: 0.862-0.951), and more clearly in participants with low ABSI (HR = 0.880; 95%CI: 0.824-0.939), or with BMI ≥ 25 kg/m2 (HR = 0.895; 95%CI: 0.837-0.958 for overweight; HR = 0.923; 95%CI: 0.848-1.005 for obese). ABSI was associated inversely in pre-menopausal women (HR = 0.810; 95%CI: 0.702-0.935; SD = 4.95) and men (HR = 0.925; 95%CI: 0.867-0.986; SD = 4.11). BMI was associated positively in men (HR = 1.148; 95%CI: 1.078-1.222; SD = 4.04 kg/m2). There was little evidence for heterogeneity according to smoking status. The associations with monocyte count and BMI were retained to at least 8 years prior to diagnosis, but the association with ABSI was observed up to 4 years prior to diagnosis and not for longer follow-up time.

CONCLUSIONS

Monocyte count is associated prospectively inversely with the risk of developing CMM in older individuals, while BMI is associated positively in men, suggesting a mechanistic involvement of factors related to monocytes and subcutaneous adipose tissue in melanoma development. An inverse association with ABSI closer to diagnosis may reflect reverse causality or glucocorticoid resistance.

S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function

BACKGROUND

The paucity of reliable biomarkers for predicting immunotherapy efficacy in patients with advanced hepatocellular carcinoma (HCC) has emerged as a burgeoning concern with the expanding use of immunotherapy. This study endeavors to delve into the potential peripheral biomarkers capable of prognosticating efficacy in HCC patients who are poised to receive anti-PD-1 monotherapy within the phase III clinical trial, KEYNOTE394. Additionally, we sought to elucidate the underlying molecular mechanisms for resistance to immune checkpoint blockade (ICB) and propose innovative combination immunotherapy strategies for future clinical application.

METHODS

Patient blood samples were collected for single-cell RNA sequencing to evaluate the immune cell signature before receiving ICB therapy. Subsequently, in vitro assays and in vivo murine model experiments were conducted to validate the mechanism that S100A9+CD14+ monocytes play a role in ICB resistance.

RESULTS

Our study demonstrates a notable enrichment of S100A9+CD14+ monocytes in the peripheral blood of patients exhibiting suboptimal responses to anti-PD-1 therapy. Moreover, we identified the Mono_S100A9 signature as a predictive biomarker, indicative of reduced efficacy in immunotherapy and decreased survival benefits across various tumor types. Mechanistically, S100A9 activates PD-L1 transcription by directly binding to the CD274 (PD-L1) gene promoter, thereby suppressing T-cell proliferation and cytotoxicity via the PD-1/PD-L1 axis, consequently diminishing the therapeutic effectiveness of subsequent anti-PD-1 treatments. Furthermore, our in vivo studies revealed that inhibiting S100A9 can synergistically enhance the efficacy of anti-PD-1 drugs in the eradication of hepatocellular carcinoma.

CONCLUSIONS

Our study underscores the significance of S100A9+CD14+ monocytes in predicting inadequate response to ICB treatment and provides insights into the monocyte cell-intrinsic mechanisms of resistance to ICB therapy. We also propose a combined therapeutic approach to enhance ICB efficacy by targeting S100A9.

A Phase 1/2 multicenter trial of DKN-01 as monotherapy or in combination with docetaxel for the treatment of metastatic castration-resistant prostate cancer (mCRPC)

BACKGROUND

Dickkopf-related protein 1 (DKK1) is a Wingless-related integrate site (Wnt) signaling modulator that is upregulated in prostate cancers (PCa) with low androgen receptor expression. DKN-01, an IgG4 that neutralizes DKK1, delays PCa growth in pre-clinical DKK1-expressing models. These data provided the rationale for a clinical trial testing DKN-01 in patients with metastatic castration-resistant PCa (mCRPC).

METHODS

This was an investigator-initiated parallel-arm phase 1/2 clinical trial testing DKN-01 alone (monotherapy) or in combination with docetaxel 75 mg/m2 (combination) for men with mCRPC who progressed on ≥1 AR signaling inhibitors. DKK1 status was determined by RNA in-situ expression. The primary endpoint of the phase 1 dose escalation cohorts was the determination of the recommended phase 2 dose (RP2D). The primary endpoint of the phase 2 expansion cohorts was objective response rate by iRECIST criteria in patients treated with the combination.

RESULTS

18 pts were enrolled into the study-10 patients in the monotherapy cohorts and 8 patients in the combination cohorts. No DLTs were observed and DKN-01 600 mg was determined as the RP2D. A best overall response of stable disease occurred in two out of seven (29%) evaluable patients in the monotherapy cohort. In the combination cohort, five out of seven (71%) evaluable patients had a partial response (PR). A median rPFS of 5.7 months was observed in the combination cohort. In the combination cohort, the median tumoral DKK1 expression H-score was 0.75 and the rPFS observed was similar between patients with DKK1 H-score ≥1 versus H-score = 0.

CONCLUSION

DKN-01 600 mg was well tolerated. DKK1 blockade has modest anti-tumor activity as a monotherapy for mCRPC. Anti-tumor activity was observed in the combination cohorts, but the response duration was limited. DKK1 expression in the majority of mCRPC is low and did not clearly correlate with anti-tumor activity of DKN-01 plus docetaxel.

High-dimensional single-cell analysis unveils distinct immune signatures of peripheral blood in patients with pancreatic ductal adenocarcinoma

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with poor response to immune checkpoint inhibitors. The mechanism of such poor response is not completely understood.

Methods

We assessed T-cell receptor (TCR) repertoire and RNA expression at the single-cell level using high-dimensional sequencing of peripheral blood immune cells isolated from PDAC patients and from healthy human controls. We validated RNA-sequencing data by performing mass cytometry (CyTOF) and by measuring serum levels of multiple immune checkpoint proteins.

Results

We found that proportions of T cells (CD45+CD3+) were decreased in PDAC patients compared to healthy controls, while proportion of myeloid cells was increased. The proportion of cytotoxic CD8+ T cells and the level of cytotoxicity per cell were increased in PDAC patients, with reduced TCR clonal diversity. We also found a significantly enriched S100A9+ monocyte population and an increased level of TIM-3 expression in immune cells of peripheral blood in PDAC patients. In addition, the serum level of soluble TIM-3 (sTIM-3) was significantly higher in PDAC patients compared to the non-PDAC participants and correlated with worse survival in two independent PDAC cohorts. Moreover, sTIM-3 exhibited a valuable role in diagnosis of PDAC, with sensitivity and specificity of about 80% in the training and validation groups, respectively. We further established an integrated model by combining sTIM-3 and carbohydrate antigen 19- 9 (CA19-9), which had an area under the curve of 0.974 and 0.992 in training and validation cohorts, respectively.

Conclusion

Our RNA-seq and proteomic results provide valuable insight for understanding the immune cell composition of peripheral blood of patients with PDAC.

Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction

Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15-60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.

Serum immune mediators as novel predictors of response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer patients with high tissue-PD-L1 expression

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related morbidity and mortality worldwide. Immune checkpoint inhibitors (ICIs) including anti-PD-1 and anti-PD-L1 antibodies, have significantly changed the treatment outcomes with better overall survival, but only 15-40% of the patients respond to ICIs therapy. The search for predictive biomarkers of responses is warranted for better clinical outcomes. We aim here to identify pre-treatment soluble immune molecules as surrogate biomarkers for tissue PD-L1 (TPD-L1) status and as predictors of response to anti-PD-1/PD-L1 therapy in NSCLC patients. Sera from 31 metastatic NSCLC patients, eligible for anti-PD-1/PD-L1 or combined chemoimmunotherapy, were collected prior to treatment. Analysis of soluble biomarkers with TPD-L1 status showed significant up/down regulation of the immune inhibitory checkpoint markers (sSiglec7, sSiglec9, sULBP4 and sPD-L2) in patients with higher TPD-L1 (TPD-L1 >50%) expression. Moreover, correlation analysis showed significant positive linear correlation of soluble PD-L1 (sPD-L1) with higher TPD-L1 expression. Interestingly, only responders in the TPD-L1 >50% group showed significant down regulation of the immune inhibitory markers (sPD-L2, sTIMD4, sNectin2 and CEA). When responders vs. non-responders were compared, significant down regulation of other immune inhibitory biomarkers (sCD80, sTIMD4 and CEA) was recorded only in responding patients. In this, the optimal cut-off values of CD80 <91.7 pg/ml and CEA <1614 pg/ml were found to be significantly associated with better progression free survival (PFS). Indeed, multivariate analysis identified the cutoff-value of CEA <1614 pg/ml as an independent predictor of response in our patients. We identified here novel immune inhibitory/stimulatory soluble mediators as potential surrogate/predictive biomarkers for TPD-L1 status, treatment response and PFS in NSCLC patients treated with anti-PD-1/PD-L1 therapy.

Biomarkers found in the tumor interstitial fluid may help explain the differential behavior among keratinocyte carcinomas

Basal Cell Carcinomas (BCC) and cutaneous Squamous Cell Carcinomas (SCC) are the most frequent types of cancer, and both originate from the keratinocyte transformation, giving rise to the group of tumors called keratinocyte carcinomas (KC). The invasive behavior is different in each group of KC and may be influenced by their tumor microenvironment. The principal aim of the study is to characterize the protein profile of the Tumor Interstitial Fluid (TIF) of KC to evaluate changes in the microenvironment that could be associated with their different invasive and metastatic capabilities. We obtained TIF from 27 skin biopsies and conducted a label-free quantitative proteomic analysis comparing 7 BCCs, 16 SCCs, and 4 Normal Skins. A total of 2945 proteins were identified, 511 of them quantified in more than half of the samples of each tumoral type. The proteomic analysis revealed differentially expressed TIF-proteins that could explain the different metastatic behavior in both KC. In detail, the SCC samples disclosed an enrichment of proteins related to cytoskeleton, such as Stratafin and Ladinin1. Previous studies found their up-regulation positively correlated with tumor progression. Furthermore, the TIF of SCC samples was enriched with the cytokines S100A8/S100A9. These cytokines influence the metastatic output in other tumors through the activation of NF-kB signaling. According to this, we observed a significant increase in nuclear NF-kB subunit p65 in SCCs but not in BCCs. In addition, the TIF of both tumors was enriched with proteins involved in the immune response, highlighting the relevance of this process in the composition of the tumor environment. Thus, the comparison of the TIF composition of both KC provides the discovery of a new set of differential biomarkers. Among them, secreted cytokines such as S100A9 may help explain the higher aggressiveness of SCCs, while Cornulin is a specific biomarker for BCCs. Finally, the proteomic landscape of TIF provides key information on tumor growth and metastasis, which can contribute to the identification of clinically applicable biomarkers that may be used in the diagnosis of KC, as well as therapeutic targets.

S100A8 and S100A9 in Cancer

S100A8 and S100A9 are Ca²⁺ binding proteins that belong to the S100 family. Primarily expressed in neutrophils and monocytes, S100A8 and S100A9 play critical roles in modulating various inflammatory responses and inflammation-associated diseases. Forming a common heterodimer structure S100A8/A9, S100A8 and S100A9 are widely reported to participate in multiple signaling pathways in tumor cells. Meanwhile, S100A8/A9, S100A8, and S100A9, mainly as promoters, contribute to tumor development, growth and metastasis by interfering with tumor metabolism and the microenvironment. In recent years, the potential of S100A8/A9, S100A9, and S100A8 as tumor diagnostic or prognostic biomarkers has also been demonstrated. In addition, an increasing number of potential therapies targeting S100A8/A9 and related signaling pathways have emerged. In this review, we will first expound on the characteristics of S100A8/A9, S100A9, and S100A8 in-depth, focus on their interactions with tumor cells and microenvironments, and then discuss their clinical applications as biomarkers and therapeutic targets. We also highlight current limitations and look into the future of S100A8/A9 targeted anti-cancer therapy.

Dynamic changes in peripheral blood monocytes early after anti-PD-1 therapy predict clinical outcomes in hepatocellular carcinoma

Immune checkpoint inhibitors are effective for advanced hepatocellular carcinoma (HCC), but there remains a need for peripheral blood biomarkers to predict the clinical response. Here, we analyzed the peripheral blood of 45 patients with advanced HCC who underwent nivolumab. During treatment, frequency of classical monocytes (CD14+CD16-) was increased on day 7, and the fold increase in the frequency on day 7 over day 0 (cMonocyteD7/D0) was significantly higher in patients with durable clinical benefit (DCB) than in patients with non-DCB (NDB). When we analyzed transcriptomes of classical monocytes, CD274, gene encoding PD-L1, was upregulated in NDB patients compared to DCB patients at day 7. Notably, gene signature of suppressive tumor-associated macrophages, or IL4l1+PD-L1+IDO1+ macrophages, was enriched after treatment in NDB patients, but not in DCB patients. Accordingly, the fold increase in the frequency of PD-L1+ classical monocytes at day 7 over day 0 (cMonocyte-PDL1D7/D0) was higher in NDB patients than DCB patients. The combined biomarker cMonocyteD7/D0/cMonocyte-PDL1D7/D0 was termed the "monocyte index", which was significantly higher in DCB patients than NDB patients. Moreover, the monocyte index was an independent prognostic factor for survival. Overall, our results suggest that early changes of circulating classical monocytes, represented as a monocyte index, could predict clinical outcomes of advanced HCC patients undergoing anti-PD-1 therapy.

Development and validation of an immune gene set-based prognostic signature in cutaneous melanoma

We aimed to fully understand the landscape of the skin cutaneous melanoma (SKCM) microenvironment and develop an immune prognostic signature that can predict the prognosis for SKCM patients. RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases. The immune-prognostic signature was constructed by LASSO Cox regression analysis. We calculated the relative abundance of 29 immune-related gene sets based on the mRNA expression profiles of 314 SKCM patients in the Cancer Genome Atlas training set. Hierarchical clustering was performed to classify SKCM patients into three clusters: immunity-high, -medium and -low. The values of our prognostic model in predicting disease progression, metastasis and immunotherapeutic responses were also validated. In conclusion, the prognostic model demonstrated a powerful ability to distinguish and predict SKCM patients' prognosis.