Concerning safety and efficacy of concurrent and consolidative durvalumab with thoracic radiotherapy in PDL1-unselected stage III non-small cell lung cancer: brief report.

INTRODUCTION: Consolidative durvalumab, an anti-programmed death ligand 1 (PDL1) immune checkpoint inhibitor, administered after concurrent chemoradiation improves outcomes of patients with locally advanced non-small cell lung cancer (NSCLC) without substantially increasing toxicities. We studied a chemotherapy-free regimen of thoracic radiotherapy (RT) with concurrent and consolidative durvalumab. METHODS: This single-arm phase II trial enrolled patients with stage III NSCLC (regardless of tumor PDL1 expression), performance status ECOG 0-1, adequate pulmonary function, and RT fields meeting standard organ constraints. Participants received two cycles of durvalumab (1500 mg every 4 weeks) concurrently with thoracic RT (60 Gy in 30 fractions), followed by up to 13 cycles of consolidative durvalumab. RESULTS: After 10 patients were enrolled, the trial was closed due to poor clinical outcomes. With a median follow-up of 12 months, five patients had disease progression and eight patients died. Six patients experienced 15 treatment-related, grade ≥3 events, including one grade 4 acute kidney injury during consolidation and two fatal pulmonary events. One fatal pulmonary event occurred during the concurrent phase in an active smoker; the other occurred after the first cycle of consolidative durvalumab. The primary endpoint of progression-free survival (PFS) at 12 months was 20% (50% for PDL1≥1% versus 0% for PDL1 unavailable or <1%). Median overall survival (OS) was not reached, 10.5 months, and 7 months, for PDL1 ≥1%, <1%, and unavailable, respectively. CONCLUSIONS: In PDL1 unselected stage III NSCLC, thoracic RT plus concurrent and consolidative durvalumab is associated with high-grade toxicity and early disease progression.

Characteristics of Long-Term Survivors With EGFR-Mutant Metastatic NSCLC.

Introduction: Characteristics of long-term survivors in EGFR-mutant (EGFRm) NSCLC are not fully understood. This retrospective analysis evaluated a multi-institution cohort of patients with EGFRm NSCLC treated in the pre-osimertinib era and sought to describe characteristics of long-term survivors. Methods: Clinical characteristics and outcomes were abstracted from the electronic medical records of patients with EGFRm metastatic NSCLC who started first-line therapy before 2015. Demographics and comutations were compared between greater than or equal to 5-year survivors and less than 5-year survivors. Multivariable Cox proportional hazard and logistic regression models were used to evaluate factors associated with survival and the odds of death within 5 years, respectively. Results: Overall, 133 patients were greater than or equal to 5-year survivors; 127 were less than 5-year survivors. Burden of pathogenic comutations including TP53 and PIK3CA was similar between greater than or equal to 5-year survivors and less than 5-year survivors. Receipt of first-line chemotherapy rather than EGFR tyrosine kinase inhibitor was similar between the groups (22% of <5-y versus 31% of ≥5-y). Baseline brain metastasis and history of smoking were associated with higher odds of death within 5 years (odds ratio = 2.16, p = 0.029 and odds ratio = 1.90, p = 0.046, respectively). Among patients without baseline brain metastases, cumulative incidence of brain metastases at 5 years was 42.3%. Both baseline and post-baseline brain metastasis were associated with worse overall survival compared with no brain metastasis (hazard ratio = 3.26, p < 0.001 and hazard ratio = 4.99, p < 0.001, respectively). Conclusions: Within patients treated for EGFRm metastatic NSCLC before 2015, absence of brain metastasis and nonsmoking status were predictive of 5-year survival. Our findings help to define a subset of patients with EGFRm NSCLC with excellent survival outcomes who may not require intensification of initial therapy.

Cmai: Predicting Antigen-Antibody Interactions from Massive Sequencing Data.

The interaction between antigens and antibodies (B cell receptors, BCRs) is the key step underlying the function of the humoral immune system in various biological contexts. The capability to profile the landscape of antigen-binding affinity of a vast number of BCRs will provide a powerful tool to reveal novel insights at unprecedented levels and will yield powerful tools for translational development. However, current experimental approaches for profiling antibody-antigen interactions are costly and time-consuming, and can only achieve low-to-mid throughput. On the other hand, bioinformatics tools in the field of antibody informatics mostly focus on optimization of antibodies given known binding antigens, which is a very different research question and of limited scope. In this work, we developed an innovative Artificial Intelligence tool, Cmai, to address the prediction of the binding between antibodies and antigens that can be scaled to high-throughput sequencing data. Cmai achieved an AUROC of 0.91 in our validation cohort. We devised a biomarker metric based on the output from Cmai applied to high-throughput BCR sequencing data. We found that, during immune-related adverse events (irAEs) caused by immune-checkpoint inhibitor (ICI) treatment, the humoral immunity is preferentially responsive to intracellular antigens from the organs affected by the irAEs. In contrast, extracellular antigens on malignant tumor cells are inducing B cell infiltrations, and the infiltrating B cells have a greater tendency to co-localize with tumor cells expressing these antigens. We further found that the abundance of tumor antigen-targeting antibodies is predictive of ICI treatment response. Overall, Cmai and our biomarker approach filled in a gap that is not addressed by current antibody optimization works nor works such as AlphaFold3 that predict the structures of complexes of proteins that are known to bind.

Brief Report: Real-World Efficacy and Safety of Sotorasib in U.S. Veterans with KRAS G12C-Mutated NSCLC.

Introduction: The KRAS G12C inhibitor sotorasib was approved for treating advanced NSCLC in the second line or later on the basis of the CodeBreaK100 trial. Nevertheless, data on the real-world efficacy and safety of sotorasib, and to its optimal dose, remain limited. Methods: Patients treated with sotorasib for NSCLC through the Veterans Health Administration were retrospectively identified from the Corporate Data Warehouse. Survival, response, and toxicity data were obtained from chart review. Results: Among the 128 patients treated with sotorasib through the Veterans Health Administration, objective response rate was 34%, progression-free survival (PFS) six months, and overall survival 12 months. Similar PFS was observed among the 16 patients who received frontline sotorasib without any prior systemic therapy for NSCLC. Toxicity leading to sotorasib interruption or dose reduction occurred in 37% of patients, whereas sotorasib discontinuation for toxicity occurred in 25%. Notably, sotorasib dose reduction was associated with substantially improved PFS and OS. Conclusions: In this real-world study, the observed efficacy of sotorasib was similar to the results of CodeBreaK100. Patients who received frontline sotorasib had similar PFS to our overall cohort, suggesting that first-line sotorasib monotherapy may benefit patients who are not eligible for chemotherapy. Toxicities leading to sotorasib interruption, dose reduction, or discontinuation were common. Sotorasib dose reduction was associated with improved survival, suggesting that sotorasib dose reduction may not compromise efficacy.

Highly variable timing renders immunotherapy efficacy and toxicity impractical biomarkers of one another in clinical practice.

Background: A useful clinical biomarker requires not only association but also a consistent temporal relationship. For instance, chemotherapy-induced neutropenia and epidermal growth-factor inhibitor-related acneiform rash both occur within weeks of treatment initiation, thereby providing information prior to efficacy assessment. Although immune checkpoint inhibitor (ICI)-associated immune-related adverse events (irAE) have been associated with therapeutic benefit, irAE may have delayed and highly variable onset. To determine whether ICI efficacy and irAE could serve as clinically useful biomarkers for predicting each other, we determined the temporal relationship between initial efficacy assessment and irAE onset in a diverse population treated with ICI. Methods: Using two-sided Fisher exact and Cochran-Armitage tests, we determined the relative timing of initial efficacy assessment and irAE occurrence in a cohort of 155 ICI-treated patients (median age 68 years, 40% women). Results: Initial efficacy assessment was performed a median of 50 days [interquartile range (IQR) 39-59 days] after ICI initiation; median time to any irAE was 77 days (IQR 28-145 days) after ICI initiation. Median time to first irAE was 42 days (IQR 20-88 days). Overall, 58% of any irAE and 47% of first irAE occurred after initial efficacy assessment. For clinically significant (grade ≥2) irAE, 60% of any and 53% of first occurred after initial efficacy assessment. The likelihood of any future irAE did not differ according to response (45% for complete or partial response vs. 47% for other cases; P=1). In landmark analyses controlling for clinical and toxicity follow-up, patients demonstrating greater tumor shrinkage at initial efficacy assessment were more likely to develop future grade ≥2 (P=0.05) and multi-organ (P=0.02) irAE. Conclusions: In contrast to that seen with chemotherapy and molecularly targeted therapies, the temporal relationship between ICI efficacy and toxicity is complex and bidirectional. In practice, neither parameter can be routinely relied on as a clinical biomarker to predict the other.

pan-MHC and cross-Species Prediction of T Cell Receptor-Antigen Binding.

Profiling the binding of T cell receptors (TCRs) of T cells to antigenic peptides presented by MHC proteins is one of the most important unsolved problems in modern immunology. Experimental methods to probe TCR-antigen interactions are slow, labor-intensive, costly, and yield moderate throughput. To address this problem, we developed pMTnet-omni, an Artificial Intelligence (AI) system based on hybrid protein sequence and structure information, to predict the pairing of TCRs of αß T cells with peptide-MHC complexes (pMHCs). pMTnet-omni is capable of handling peptides presented by both class I and II pMHCs, and capable of handling both human and mouse TCR-pMHC pairs, through information sharing enabled this hybrid design. pMTnet-omni achieves a high overall Area Under the Curve of Receiver Operator Characteristics (AUROC) of 0.888, which surpasses competing tools by a large margin. We showed that pMTnet-omni can distinguish binding affinity of TCRs with similar sequences. Across a range of datasets from various biological contexts, pMTnet-omni characterized the longitudinal evolution and spatial heterogeneity of TCR-pMHC interactions and their functional impact. We successfully developed a biomarker based on pMTnet-omni for predicting immune-related adverse events of immune checkpoint inhibitor (ICI) treatment in a cohort of 57 ICI-treated patients. pMTnet-omni represents a major advance towards developing a clinically usable AI system for TCR-pMHC pairing prediction that can aid the design and implementation of TCR-based immunotherapeutics.

A phase II clinical trial evaluating the safety and efficacy of durvalumab as first line therapy in advanced and metastatic non-small cell lung cancer patients with Eastern Cooperative Oncology Group performance status of 2.

Background: Approximately 30-40% of patients with advanced and metastatic non-small cell lung cancer (NSCLC) present with an impaired performance status (PS). There are limited prospective data on the safety and efficacy of durvalumab in these patients. Methods: In this single-arm phase II clinical trial (NCT02879617), patients with previously untreated Stage IIIB/IV NSCLC and ECOG PS of 2 received durvalumab 1500 mg every 28 days until progression or unacceptable toxicity. The primary endpoints were overall survival (OS) and safety determined by grade ≥3 treatment-related adverse events (TRAEs). Findings: Between April 2017 and March 2021, 50 patients were enrolled, of whom 47 received durvalumab. With a median follow-up of 28 months, median OS was 6 months (95% CI 4-10). TRAEs grade 3 occurred in nine of 47 patients (19%, 95% CI 9%-33%). OS in patients with a PD-L1 TPS of 0, 1-49%, and ≥50% was six months (95% CI 3-15), 11 months (95% CI 4-16), and 11 months (95% CI 0-not reached (NR)), respectively. Health related quality of life (HQRL) assessed at baseline and during therapy demonstrated no statistically significant change over the course of treatment. Interpretation: This study demonstrates that single agent durvalumab is safe and well tolerated in the 1st line treatment of patients with advanced NSCLC and ECOG PS of 2, with an encouraging OS benefit in patients with PD-L1 positive tumors. This trial is amongst the largest prospective studies evaluating durvalumab in the 1st line treatment of advanced stage NSCLC and a PS of 2. Funding: AstraZeneca, NCI P30CA047904.