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BackgroundLymphocyte-activation gene 3 (LAG-3) is an inhibitory immunoreceptor that negatively regulates T-cell activation. This paper presents preclinical characterization of the LAG-3 inhibitor, ieramilimab (LAG525), and phase I data for the treatment of patients with advanced/metastatic solid tumors with ieramilimab ±the anti-programmed cell death-1 antibody, spartalizumab.MethodsEligible patients had advanced/metastatic solid tumors and progressed after, or were unsuitable for, standard-of-care therapy, including checkpoint inhibitors in some cases. Patients received ieramilimab ±spartalizumab across various dose-escalation schedules. The primary objective was to assess the maximum tolerated dose (MTD) or recommended phase II dose (RP2D).ResultsIn total, 255 patients were allocated to single-agent ieramilimab (n=134) and combination (n=121) treatment arms. The majority (98%) had received prior antineoplastic therapy (median, 3). Four patients experienced dose-limiting toxicities in each treatment arm across various dosing cohorts. No MTD was reached. The RP2D on a 3-week schedule was declared as 400 mg ieramilimab plus 300 mg spartalizumab and, on a 4-week schedule (once every 4 weeks; Q4W), as 800 mg ieramilimab plus 400 mg spartalizumab; tumor target (LAG-3) suppression with 600 mg ieramilimab Q4W was predicted to be similar to the Q4W, RP2D schedule. Treatment-related adverse events (TRAEs) occurred in 75 (56%) and 84 (69%) patients in the single-agent and combination arms, respectively. Most common TRAEs were fatigue, gastrointestinal, and skin disorders, and were of mild severity; seven patients experienced at least one treatment-related serious adverse event in the single-agent (5%) and combination group (5.8%). Antitumor activity was observed in the combination arm, with 3 (2%) complete responses and 10 (8%) partial responses in a mixed population of tumor types. In the combination arm, eight patients (6.6%) experienced stable disease for 6 months or longer versus six patients (4.5%) in the single-agent arm. Responding patients trended towards having higher levels of immune gene expression, including CD8 and LAG3, in tumor tissue at baseline.ConclusionsIeramilimab was well tolerated as monotherapy and in combination with spartalizumab. The toxicity profile of ieramilimab in combination with spartalizumab was comparable to that of spartalizumab alone. Modest antitumor activity was seen with combination treatment.Trial registration numberNCT02460224.

Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes. It is possible to call single-nucleotide variant (SNV) in cell-free DNA (cfDNA), but the accuracy of detection is often affected by low tumour cfDNA content. Here, the authors develop a method, cfSNV, and show that it can be used even for medium-coverage whole exome sequencing of cfDNA.

PurposeImmune checkpoint inhibitors (ICIs) have shown durable responses in various malignancies. However, the response to ICI therapy is unpredictable, and investigation of predictive biomarkers needs to be improved.Experimental designIn total, 120 patients receiving ICI therapy and 40 patients receiving non-ICI therapy were enrolled. Peripheral blood immune cell markers (PBIMs), as liquid biopsy biomarkers, were analyzed by flow cytometry before ICI therapy, and before the first evaluation. In the ICI cohort, patients were randomly divided into training (n = 91) and validation (n = 29) cohorts. Machine learning algorithms were applied to construct the prognostic and predictive immune-related models.ResultsUsing the training cohort, a peripheral blood immune cell-based signature (BICS) based on four hub PBIMs was developed. In both the training and the validation cohorts, and the whole cohort, the BICS achieved a high accuracy for predicting overall survival (OS) benefit. The high-BICS group had significantly shorter progression-free survival and OS than the low-BICS group. The BICS demonstrated the predictive ability of patients to achieve durable clinical outcomes. By integrating these PBIMs, we further constructed and validated the support vector machine-recursive and feature elimination classifier model, which robustly predicts patients who will achieve optimal clinical benefit.ConclusionsDynamic PBIM-based monitoring as a noninvasive, cost-effective, highly specific and sensitive biomarker has broad potential for prognostic and predictive utility in patients receiving ICI therapy.

BackgroundTumor immune cells influence the efficacy of immune-checkpoint inhibitors (ICIs) and many efforts aim at identifying features of tumor immune microenvironment able to predict benefit from ICIs in proficient mismatch repair (pMMR)/microsatellite stable (MSS) metastatic colorectal cancer (mCRC).MethodsWe characterized tumor immune cell infiltrate, by assessing tumor-infiltrating lymphocytes (TILs), Immunoscore, Immunoscore-IC, and programmed death ligand-1 (PD-L1) expression in tumor samples of patients with mCRC enrolled in the AtezoTRIBE study, a phase II randomized trial comparing FOLFOXIRI/bevacizumab/atezolizumab to FOLFOXIRI/bevacizumab, with the aim of evaluating the prognostic and predictive value of these features.ResultsOut of 218 patients enrolled, 181 (83%), 77 (35%), 157 (72%) and 162 (74%) specimens were successfully tested for TILs, Immunoscore, Immunoscore-IC and PD-L1 expression, respectively, and 69 (38%), 45 (58%), 50 (32%) and 21 (13%) tumors were classified as TILs-high, Immunoscore-high, Immunoscore-IC-high and PD-L1-high, respectively. A poor agreement was observed between TILs and Immunoscore or Immunoscore-IC (K of Cohen <0.20). In the pMMR population, longer progression-free survival (PFS) was reported for Immunoscore-high and Immunoscore-IC-high groups compared with Immunoscore-low (16.4 vs 12.2 months; HR: 0.55, 95% CI: 0.30 to 0.99; p=0.049) and Immunoscore-IC-low (14.8 vs 11.5 months; HR: 0.55, 95% CI: 0.35 to 0.85; p=0.007), respectively, with a significant interaction effect between treatment arms and Immunoscore-IC (p for interaction: 0.006) and a trend for Immunoscore (p for interaction: 0.13). No PFS difference was shown according to TILs and PD-L1 expression. Consistent results were reported in the overall population.ConclusionsThe digital evaluation of tumor immune cell infiltrate by means of Immunoscore-IC or Immunoscore identifies the subset of patients with pMMR mCRC achieving more benefit from the addition of the anti-PD-L1 to the upfront treatment. Immunoscore-IC stands as the most promising predictor of benefit from ICIs.

Background Immunotherapy has significantly improved survival of esophageal squamous cell cancer (ESCC) patients, however the clinical benefit was limited to only a small portion of patients. This study aimed to perform a deep learning signature based on H&E-stained pathological specimens to accurately predict the clinical benefit of PD-1 inhibitors in ESCC patients. Methods ESCC patients receiving PD-1 inhibitors from Shandong Cancer Hospital were included. WSI images of H&E-stained histological specimens of included patients were collected, and randomly divided into training (70%) and validation (30%) sets. The labels of images were defined by the progression-free survival (PFS) with the interval of 4 months. The pretrained ViT model was used for patch-level model training, and all patches were projected into probabilities after linear classifier. Then the most predictive patches were passed to RNN for final patient-level prediction to construct ESCC-pathomics signature (ESCC-PS). Accuracy rate and survival analysis were performed to evaluate the performance of ViT-RNN survival model in validation cohort. Results 163 ESCC patients receiving PD-1 inhibitors were included for model training. There were 486,188 patches of 1024*1024 pixels from 324 WSI images of H&E-stained histological specimens after image pre-processing. There were 120 patients with 227 images in training cohort and 43 patients with 97 images in validation cohort, with balanced baseline characteristics between two groups. The ESCC-PS achieved an accuracy of 84.5% in the validation cohort, and could distinguish patients into three risk groups with the median PFS of 2.6, 4.5 and 12.9 months (P < 0.001). The multivariate cox analysis revealed ESCC-PS could act as an independent predictor of survival from PD-1 inhibitors (P < 0.001). A combined signature incorporating ESCC-PS and expression of PD-L1 shows significantly improved accuracy in outcome prediction of PD-1 inhibitors compared to ESCC-PS and PD-L1 anlone, with the area under curve value of 0.904, 0.924, 0.610 for 6-month PFS and C-index of 0.814, 0.806, 0.601, respectively. Conclusions The outcome supervised pathomics signature based on deep learning has the potential to enable superior prognostic stratification of ESCC patients receiving PD-1 inhibitors, which convert the images pixels to an effective and labour-saving tool to optimize clinical management of ESCC patients.

Immune checkpoint inhibitors (ICIs) have been introduced in breast cancer (BC) treatment and better biomarkers are needed to predict benefit. Circulating tumor cells (CTCs) are prognostic in BC, but knowledge is limited on CTCs in the context of ICI therapy. In this study, serial sampling of CTCs (CellSearch system) was evaluated in 82 patients with metastatic BC enrolled in two randomized trials investigating ICI plus chemotherapy. Programmed death‐ligand 1 (PD‐L1) expression on CTCs was also measured. Patients with ≥ 2 CTCs per 7.5 mL at baseline had gene expression profiles in tumor suggestive of increased T‐cell activity, including increased tumor inflammation signature (TIS) in both triple‐negative (P = 0.010) and hormone receptor‐positive (P = 0.024) disease. Patients with luminal A BC had higher CTC levels. The association between CTC status and outcome was most apparent 4 weeks into therapy. PD‐L1 expression in CTCs was observed in 6/17 CTC‐positive patients and was associated with inferior survival. In conclusion, our study indicates that CTC numbers may inform on tumor immune composition, as well as prognosis. These findings suggest a potential of using CTCs as an accessible biomarker source in BC patients treated with immunotherapy. In this explorative biomarker analysis, we assessed serial sampling of circulating tumor cells (CTCs) with CellSearch in two randomized trials testing immune checkpoint inhibitors (ICIs) in metastatic breast cancer. Our data demonstrate a prognostic potential of CTCs, most apparent 4 weeks into ICI therapy. Furthermore, higher CTC counts were associated with increased markers of tumor immune activity.

BackgroundImmune checkpoint inhibitors (ICIs) are recommended to treat patients with deficient mismatch repair/microsatellite instability high (dMMR/MSI-H) metastatic colorectal cancer (mCRC). Pivotal trials have fixed a maximum ICI duration of 2 years, without a compelling rationale. A shorter treatment duration has the potential to improve patients' quality of life and reduce both toxicity and cost without compromising efficacy. Here we examine whether early treatment discontinuation (ETD) before 13 months in patients without progressive disease (PD) can lead to similar long-term disease control compared with a longer treatment duration (LTD).MethodsTo assess whether ETD is associated with similar outcomes compared with LTD, we assembled an international cohort of patients with dMMR/MSI-H mCRC treated with ICIs who stopped treatment for a reason other than PD within 395 days (ETD group) and compared them to those who continued for >395 days (LTD group). Outcomes were adjusted for patient/tumor characteristics. Primary endpoint was progression-free survival (PFS) and secondary endpoints were objective response rate (ORR), overall survival (OS) and safety.ResultsOf 976 patients, 137 and 394 were allocated to the ETD and LTD groups, respectively. In the ETD group, treatment was discontinued due to toxicity (n=56), objective response (n=43), surgery (n=28), patient decision (n=2) or other reasons (n=8). Baseline characteristics were well balanced between the two groups: 22% in both groups received both anti-programmed death-(ligand) 1 (anti-PD-(L)1) + anti-cytotoxic T-lymphocyte antigen-4 (anti-CTLA-4); all others received anti-PD-(L)1 monotherapy. ORR to ICIs was 81% in both groups. Median duration of treatment was ~7 months in the ETD and ~24 months in the LTD group. After a median follow-up of 44 months (IQR: 30–67), similar PFS (HR: 0.92, 95% CI: 0.60 to 1.40, p=0.69) and OS (HR: 1.15, 95% CI: 0.66 to 1.99, p=0.62) from the start of ICIs were observed in ETD and LTD patients. In the ETD group, 28 (20%) patients had a PFS event and 9 restarted ICIs with a disease control rate of 66%.ConclusionsIn our international series of dMMR/MSI-H mCRC, ETD of ICIs in the absence of PD did not seem detrimental in terms of PFS and OS compared with continuing treatment beyond 1 year. Randomized clinical trials to compare short and long treatment duration are now warranted.

Background Immune checkpoint inhibitors (ICIs), particularly PD-1/PD-L1 inhibitors, have demonstrated significant survival benefits in treating recurrent or metastatic nasopharyngeal carcinoma (R/M-NPC). While baseline peripheral blood lymphocyte subsets have been identified as prognostic biomarkers in various cancers treated with ICIs, their relevance in R/M-NPC has not been extensively studied. Methods This post hoc analysis used data from 153 R/M-NPC patients treated with PD-L1 inhibitor monotherapy in the phase 2 trial KL167-2-05-CTP. The lymphocyte subsets, including total T cells, CD4/CD8 ratio, helper T cells, suppressor cytotoxic T cells, NK cells, and B cells, were tested by flow cytometry. These subsets were grouped using optimal cutoff values identified by the Maximally Selected Log-rank Statistic. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan–Meier and Cox regression analysis, and logistic regression analysis evaluated the associations with objective response rate (ORR) and disease control rate (DCR). Results Patients with lower NK cell percentages showed significantly longer OS (26.3 vs. 12.1 months, p  < 0.001) and PFS (5.5 vs. 3.7 months, p  < 0.001) compared to those with higher NK cell percentages. No significant differences in OS or PFS were observed for other lymphocyte subsets. High NK cell percentages were identified as risk factors for shorter OS (HR, 2.49) and PFS (HR, 1.62). There were no significant differences in ORR and DCR between high and low lymphocyte subsets. Conclusion Lower baseline NK cell percentages are associated with improved OS and PFS in R/M-NPC patients undergoing PD-L1 inhibitor therapy.

IntroductionDespite significant successes, immune checkpoint blockade fails to achieve clinical responses in a significant proportion of patients, predictive markers for responses are imperfect and immune-related adverse events (irAEs) are unpredictable. We used T-cell receptor (TCR) sequencing to systematically analyze prospectively collected patient blood samples from a randomized clinical trial of dual immune checkpoint inhibitor therapy to evaluate changes in the T-cell repertoire and their association with response and irAEs.MethodsPatients with immunotherapy-naïve metastatic non-small cell lung cancer (NSCLC) were treated with ipilimumab and nivolumab according to trial protocol (LONESTAR, NCT03391869). Blood samples were systematically obtained at baseline (n=107), after 12 weeks of ipilimumab and nivolumab (n=91), and at the time of grade ≥2 irAEs (n=77). For analysis of T-cell repertoire, we performed immunoSEQ to assess the complementary determining region 3β region of the TCR involved in antigen binding.ResultsA total of 250 samples from 119 patients were analyzed. Patients who had a response to therapy exhibited greater T-cell diversity at baseline. Interestingly, patients with irAEs demonstrated lower T-cell richness at the time of toxicity compared with those without irAEs.ConclusionOur study highlights the potential impact of peripheral blood T-cell repertoire on clinical response and toxicities from the combination of ipilimumab and nivolumab in patients with metastatic NSCLC. These findings suggest that analysis of peripheral blood T-cell repertoire may help to guide patient selection for treatment with ipilimumab and nivolumab.Trial registration numberNCT03391869.

BackgroundAn increased incidence of thrombotic complications associated with an increased mortality rate has been observed under immune checkpoint inhibition (ICI). Recent investigations on the coagulation pathways have highlighted the direct role of key coagulatory proteins and platelets in cancer initiation, angiogenesis and progression. The aim of this study was to evaluate the prognostic value of von Willebrand factor (vWF) and its regulatory enzyme a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13), D-dimers and platelets in a cohort of patients with metastatic melanoma receiving ICI.MethodsIn a prospective cohort of 83 patients with metastatic melanoma, we measured the systemic levels of vWF-antigen (vWF:Ag), ADAMTS13 activity, D-dimers and platelets, before the beginning of the treatment (baseline), and 6, 12 and 24 weeks after. In parallel, we collected standard biological parameters used in clinical routine to monitor melanoma response (lactate deshydrogenase (LDH), S100). The impact of neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) on overall survival (OS) in patients receiving ICI was assessed. Univariable and multivariable Cox proportional models were then used to investigate any potential association of these parameters to clinical progression (progression-free survival (PFS) and OS). Baseline values and variations over therapy course were compared between primary responders and resistant patients.ResultsPatients with melanoma present with dysregulated levels of vWF:Ag, ADAMTS13 activity, D-dimers, LDH, S100 and CRP at the beginning of treatment. With a median clinical follow-up of 26 months, vWF:Ag interrogated as a continuous variable was significantly associated with PFS in univariate and multivariate analysis (HR=1.04; p=0.007). Lower values of vWF:Ag at baseline were observed in the primary responders group (median: 29.4 µg/mL vs 32.9 µg/mL; p=0.048) when compared with primary resistant patients. As for OS, we found an association with D-dimers and ADAMTS13 activity in univariate analysis and vWF:Ag in univariate and multivariate analysis including v-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutation and Eastern Cooperative Oncology Group (ECOG) performance status. Follow-up over the course of treatment depicts different evolution profiles for vWF:Ag between the primary response and resistance groups.ConclusionsIn this prospective cohort, coagulatory parameters such as ADAMTS13 activity and D-dimers are associated with OS but baseline vWF:Ag levels appeared as the only parameter associated with response and OS to ICI. This highlights a potential role of vWF as a biomarker to monitor ICI response of patients with malignant melanoma.