Background: Neoadjuvant chemoimmunotherapy for non-small cell lung cancer (NSCLC) has improved pathological responses and survival rates compared with chemotherapy alone, leading to Food and Drug Administration (FDA) approval of nivolumab plus chemotherapy for resectable stage IB-IIIA NSCLC (AJCC 7th edition) without ALK or EGFR alterations. Unfortunately, a considerable percentage of tumors do not completely respond to therapy, which has been associated with early disease progression. So far, it is impossible to predict these events due to lack of knowledge. In this study, we characterized the gene expression profile of tumor samples to identify new biomarkers and mechanisms behind tumor responses to neoadjuvant chemoimmunotherapy and disease recurrence after surgery. Methods: Tumor bulk RNA sequencing was performed in 16 pretreatment and 36 post-treatment tissue samples from 41 patients with resectable stage IIIA NSCLC treated with neoadjuvant chemoimmunotherapy from NADIM trial. A panel targeting 395 genes related to immunological processes was used. Tumors were classified as complete pathological response (CPR) and non-CPR, based on the total absence of viable tumor cells in tumor bed and lymph nodes tested at surgery. Differential-expressed genes between groups and pathway enrichment analysis were assessed using DESeq2 and gene set enrichment analysis. CIBERSORTx was used to estimate the proportions of immune cell subtypes. Results: CPR tumors had a stronger pre-established immune infiltrate at baseline than non-CPR, characterized by higher levels of IFNG, GZMB, NKG7, and M1 macrophages, all with a significant area under the receiver operating characteristic curve (ROC) >0.9 for CPR prediction. A greater effect of neoadjuvant therapy was also seen in CPR tumors with a reduction of tumor markers and IFNγ signaling after treatment. Additionally, the higher expression of several genes, including AKT1, BST2, OAS3, or CD8B; or higher dendritic cells and neutrophils proportions in post-treatment non-CPR samples, were associated with relapse after surgery. Also, high pretreatment PD-L1 and tumor mutational burden levels influenced the post-treatment immune landscape with the downregulation of proliferation markers and type I interferon signaling molecules in surgery samples. Conclusions: Our results reinforce the differences between CPR and non-CPR responses, describing possible response and relapse immune mechanisms, opening the possibility of therapy personalization of immunotherapy-based regimens in the neoadjuvant setting of NSCLC.

Purpose: Characterization of the T-cell receptor (TCR) repertoire may be a promising source for predictive biomarkers of pathologic response to immunotherapy in locally advanced non–small cell lung cancer (NSCLC). Experimental Design: In this study, next-generation TCR sequencing was performed in peripheral blood and tissue samples of 40 patients with NSCLC, before and after neoadjuvant chemoimmunotherapy (NADIM clinical trial, NCT03081689), considering their complete pathologic response (CPR) or non-CPR. Beyond TCR metrics, tissue clones were ranked by their frequency and spatiotemporal evolution of top 1% clones was determined. Results: We have found a positive association between an uneven TCR repertoire in tissue samples at diagnosis and CPR at surgery. Moreover, TCR most frequently ranked clones (top 1%) present in diagnostic biopsies occupied greater frequency in the total clonal space of CPR patients, achieving an AUC ROC to identify CPR patients of 0.967 (95% confidence interval, 0.897–1.000; P = 0.001), and improving the results of PD-L1 tumor proportion score (TPS; AUC = 0.767; P = 0.026) or tumor mutational burden (TMB; AUC = 0.550; P = 0.687). Furthermore, tumors with high pretreatment top 1% clonal space showed similar immune cell populations but a higher immune reactive gene expression profile. Finally, the selective expansion of pretreatment tissue top 1% clones in peripheral blood of CPR patients suggests also a peripheral immunosurveillance, which could explain the high survival rate of these patients. Conclusions: We have identified two parameters derived from TCR repertoire analysis that could outperform PD-L1 TPS and TMB as predictive biomarkers of CPR after neoadjuvant chemoimmunotherapy, and unraveled possible mechanisms of CPR involving enhanced tumor immunogenicity and peripheral immunosurveillance.

Background: Artificial intelligence (AI) has contributed substantially in recent years to the resolution of different biomedical problems, including cancer. However, AI tools with significant and widespread impact in oncology remain scarce. The goal of this study is to present an AI-based solution tool for cancer patients data analysis that assists clinicians in identifying the clinical factors associated with poor prognosis, relapse and survival, and to develop a prognostic model that stratifies patients by risk. Materials and Methods: We used clinical data from 5275 patients diagnosed with non-small cell lung cancer, breast cancer, and non-Hodgkin lymphoma at Hospital Universitario Puerta de Hierro-Majadahonda. Accessible clinical parameters measured with a wearable device and quality of life questionnaires data were also collected. Results: Using an AI-tool, data from 5275 cancer patients were analyzed, integrating clinical data, questionnaires data, and data collected from wearable devices. Descriptive analyses were performed in order to explore the patients’ characteristics, survival probabilities were calculated, and a prognostic model identified low and high-risk profile patients. Conclusion: Overall, the reconstruction of the population’s risk profile for the cancer-specific predictive model was achieved and proved useful in clinical practice using artificial intelligence. It has potential application in clinical settings to improve risk stratification, early detection, and surveillance management of cancer patients.

Purpose: Follicular lymphoma (FL) is the most frequent indolent non-Hodgkin lymphoma. Around 20% of patients suffer early disease progression within 24 months (POD24) of diagnosis. This study examined the significance of circulating tumor DNA (ctDNA) in predicting response to therapy and POD24 in patients with FL. Experimental Design: We collected 100 plasma samples, before and during the treatment, from 36 patients with FL prospectively enrolled in 8 Spanish hospitals. They were treated with a chemotherapy-rituximab regimen and followed up for a median of 3.43 years. We performed targeted deep sequencing in cell-free DNA (cfDNA) and tumor genomic DNA from 31 diagnostic biopsy samples. Results: Of the alterations detected in the diagnostic tissue samples, 73% (300/411) were also identified in basal cfDNA. The mean numbers of alterations per basal cfDNA sample in patients who suffered progression of disease within 24 months (POD24-pos) or did not achieve complete response (non-CR) were significantly higher than in POD24-neg or CR patients (unpaired samples t test, P = 0.0001 and 0.001, respectively). Pretreatment ctDNA levels, as haploid genome equivalents per milliliter of plasma, were higher in patients without CR (P = 0.02) and in POD24-pos patients compared with POD24-neg patients (P < 0.001). Dynamic analysis showed that ctDNA levels decreased dramatically after treatment, although the reduction was more significant in patients with CR and POD24-neg patients. Conclusions: Basal ctDNA levels are associated with the risk of early progression and response to treatment in FL. cfDNA monitoring and genotyping during treatment and follow-up predict response to treatment and early progression.

Lung cancer continues to be the leading cause of cancer mortality and a serious health problem despite the numerous advances made in the last decade and the rapid advance of research in this field.... Tweetable abstract The time has come to offer targeted therapy to patients with earlier-stage non-small-cell lung cancer, which could represent an important qualitative leap in the treatment of lun... Lay abstract Despite major therapeutic advances over the last decade, lung cancer continues to present the highest mortality rate of all cancers. Precision and personalized therapy directed at spec...

Background Loss of human leukocyte antigen (HLA) class I expression and loss of heterozygosity (LOH) are common events implicated in the primary resistance of non-small cell lung cancer (NSCLC) to immunotherapy. However, there is no data on perioperative chemoimmunotherapy (ChIO) efficacy or response mechanisms in the context of HLA class I defects. Methods Baseline HLA class I tumor status (HLA-deficient (HLA-DEF) or HLA-proficient (HLA-PRO)) was determined by DNA LOH combined with immunohistochemistry for protein levels in tissue of 24 patients with NSCLC treated with perioperative nivolumab plus chemotherapy from NADIM trial (NCT03081689). We integrated HLA tumor status with molecular data (programmed death-ligand 1 (PD-L1), TMB, TCR repertoire, TILs populations, bulk RNA-seq, and spatial transcriptomics (ST)) and clinical outcomes (pathological response and survival data) to study the activity of perioperative ChIO considering HLA class I defects. Results HLA-DEF tumors comprised 41.7% of analyzed tumors and showed a desert-like microenvironment at baseline, with lower PD-L1 levels and reduced immune infiltrate. However, perioperative ChIO induced similar complete pathological response (CPR) rates in both HLA-DEF and PRO tumors (50% and 60% respectively, p=0.670), as well as 3-year survival rates: Progression-free survival (PFS) and overall survival (OS) of 70% (95% CI 32.9% to 89.2%) for HLA-DEF, and PFS 71.4% (95% CI 40.6% to 88.2%) and OS 92.9% (95% CI 59.1% to 99.0%) for HLA-PRO (log-rank PFS p=0.909, OS p=0.137). Proof-of-concept ST analysis of a CPR HLA-DEF tumor after ChIO showed a strong immune response with tertiary lymphoid structures (TLS), CD4+T cells with HLA class II colocalization, and activated CD8+T cells. Conclusions Our findings highlight the activity of perioperative ChIO, and the potential role of TLS and T-cell immune response, in NSCLC HLA-DEF tumors.