Immune Profiling Uncovers Memory T-Cell Responses with a Th17 Signature in Cancer Patients with Previous SARS-CoV-2 Infection Followed by mRNA Vaccination.

It is unclear whether patients with cancer present inherently impaired responses to COVID-19 and vaccination due to their treatments, neoplastic diseases or both. To address this question, immune profiling was performed in three cohorts of healthy donors and oncologic patients: infected with SARS-CoV-2, BNT162b2-vaccinated, and with previous COVID-19 disease and subsequently vaccinated. Cancer patients showed good antibody responses to vaccination, but poor induction of T-cell responses towards the S protein when compared to infection. Following natural infection, the major targets for T-cells were the SARS-CoV-2 structural proteins M and S, but not the N protein. Similar to antibody titers, the T-cell responses quickly decayed after six months post-vaccination. Significant memory T-cell expansion was observed in vaccinated donors only if previously diagnosed with COVID-19 before undergoing vaccination. Oncologic patients with previous COVID-19 followed by vaccination exhibited potent IL-17+ CD4 and CD8 T-cell responses and elevated numbers of circulating neutrophils in peripheral blood.

Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation.

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Functional systemic CD4 immunity is required for clinical responses to PD-L1/PD-1 blockade therapy.

The majority of lung cancer patients progressing from conventional therapies are refractory to PD-L1/PD-1 blockade monotherapy. Here, we show that baseline systemic CD4 immunity is a differential factor for clinical responses. Patients with functional systemic CD4 T cells included all objective responders and could be identified before the start of therapy by having a high proportion of memory CD4 T cells. In these patients, CD4 T cells possessed significant proliferative capacities, low co-expression of PD-1/LAG-3 and were responsive to PD-1 blockade ex vivo and in vivo. In contrast, patients with dysfunctional systemic CD4 immunity did not respond even though they had lung cancer-specific T cells. Although proficient in cytokine production, CD4 T cells in these patients proliferated very poorly, strongly co-upregulated PD-1/LAG-3, and were largely refractory to PD-1 monoblockade. CD8 immunity only recovered in patients with functional CD4 immunity. T-cell proliferative dysfunctionality could be reverted by PD-1/LAG-3 co-blockade. Patients with functional CD4 immunity and PD-L1 tumor positivity exhibited response rates of 70%, highlighting the contribution of CD4 immunity for efficacious PD-L1/PD-1 blockade therapy.

PD-L1 Expression in Systemic Immune Cell Populations as a Potential Predictive Biomarker of Responses to PD-L1/PD-1 Blockade Therapy in Lung Cancer.

PD-L1 tumor expression is a widely used biomarker for patient stratification in PD-L1/PD-1 blockade anticancer therapies, particularly for lung cancer. However, the reliability of this marker is still under debate. Moreover, PD-L1 is widely expressed by many immune cell types, and little is known on the relevance of systemic PD-L1⁺ cells for responses to immune checkpoint blockade. We present two clinical cases of patients with non-small cell lung cancer (NSCLC) and PD-L1-negative tumors treated with atezolizumab that showed either objective responses or progression. These patients showed major differences in the distribution of PD-L1 expression within systemic immune cells. Based on these results, an exploratory study was carried out with 32 cases of NSCLC patients undergoing PD-L1/PD-1 blockade therapies, to compare PD-L1 expression profiles and their relationships with clinical outcomes. Significant differences in the percentage of PD-L1⁺ CD11b⁺ myeloid cell populations were found between objective responders and non-responders. Patients with percentages of PD-L1⁺ CD11b⁺ cells above 30% before the start of immunotherapy showed response rates of 50%, and 70% when combined with memory CD4 T cell profiling. These findings indicate that quantification of systemic PD-L1⁺ myeloid cell subsets could provide a simple biomarker for patient stratification, even if biopsies are scored as PD-L1 null.