Immunotherapy with Immune Checkpoint Inhibitors (ICIs) has demonstrated a profitable performance for Non-Small Cell Lung Cancer (NSCLC) cancer treatment in some patients; however, there is still a percentage of patients in whom immunotherapy does not provide the desired results regarding beneficial outcomes. Therefore, obtaining predictive biomarkers for ICI response will improve the treatment management in clinical practice. In this sense, liquid biopsy appears as a promising method to obtain samples in a minimally invasive and non-biased way. In spite of its evident potential, the use of these circulating biomarkers is still very limited in the real clinical practice, mainly due to the huge heterogeneity among the techniques, the lack of consensus, and the limited number of patients included in these previous studies. In this work, we review the pros and cons of the different proposed biomarkers, such as soluble PD-L1, circulating non-coding RNA, circulating immune cells, peripheral blood cytokines, and ctDNA, obtained from liquid biopsy to predict response to ICI treatment at baseline and to monitor changes in tumor and tumor microenvironment during the course of the treatment in NSCLC patients.

Background: We explore the utility of TruSight Tumor 170 panel (TST170) for detecting somatic mutations in tumor and cfDNA from locoregional recurrent and/or metastatic head and neck squamous cell carcinoma (HNSCC).Methods: Targeted NGS of tumor DNA and plasma cfDNA was performed using TST170 panel. In addition, a set of somatic mutations previously described in HNSCC were selected for validating in tumor, plasma, and saliva by digital droplet PCR.Results: The TST170 panel identified 13 non‐synonymous somatic mutations, of which five were detected in tumoral tissue, other five in plasma cfDNA, and three in both tissue and plasma cfDNA. Of the eight somatic mutations identified in tissue, three were also identified in plasma cfDNA, showing an overall concordance rate of 37.5%.Conclusions: This preliminary study shows the possibility to detect somatic mutations in tumor and plasma of HNSCC patients using a single assay that would facilitate the clinical implementation of personalized medicine in the clinic.

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment, particularly in advanced non-small cell lung cancer (NSCLC) and muscle-invasive bladder cancer (MIBC). However, identifying reliable predictive biomarkers for ICI response remains a significant challenge. In this study, we analyzed real-world cohorts of advanced NSCLC and MIBC patients treated with ICI as first-line therapy. Tumor samples underwent Whole Genome Sequencing (WGS) to identify specific somatic variants and assess tumor mutational burden (TMB). Additionally, mutational signature extraction and pathway enrichment analyses were performed to uncover the underlying mechanisms of ICI response. We also characterized HLA-I haplotypes and investigated LINE-1 retrotransposition. Distinct mutation patterns were identified in patients who responded to treatment, suggesting potential biomarkers for predicting ICI effectiveness. In NSCLC, tumor mutational burden (TMB) did not differ significantly between responders and non-responders, while in MIBC, higher TMB was linked to better responses. Specific mutational signatures and HLA haplotypes were associated with ICI response in both cancers. Pathway analysis showed that NSCLC responders had active inflammatory and immune pathways, while pathways enriched in non-responders related to FGFR3 and neural crest differentiation, associated to resistance mechanisms. In MIBC, responders had alterations in DNA repair, leading to more neoantigens and a stronger ICI response. Importantly, for the first time, we found that LINE-1 activation was positively linked to ICI response, especially in MIBC. These findings reveal promising biomarkers and mechanistic insights, offering a new perspective on predicting ICI response and opening up exciting possibilities for more personalized immunotherapy strategies in NSCLC and MIBC.

Immunotherapy has opened new avenues of treatment for patients with advanced non-small cell lung cancer (NSCLC) without previous hope of survival. Unfortunately, only a small percentage of patients benefit from it and there is not an effective biomarker to predict patients' response. Since T cells are key effectors of antitumor immunity, T cell receptor (TCR) has emerged as a potential predictive biomarker. Here, we evaluated the potential of baseline TCR repertoire, as a predictive biomarker in advanced NSCLC patients treated with pembrolizumab at first-line. After obtaining peripheral blood and tissue samples at baseline, next-generation sequencing targeting TCRβ/γ was performed. We found an uneven tumor-infiltrating TCRβ repertoire, and the use of various tumor-infiltrating and circulating TRBV/J genes were able of predicting the immunotherapy response. Our results support the potential of evaluating tissue and circulating TCRβ repertoire prior to pembrolizumab, revealing it as a promising immunotherapy response biomarker in NSCLC patients.

The relevant role of LINE-1 (L1) retrotransposition in cancer has been recurrently demonstrated in recent years. However, their repetitive nature hampers their identification and detection, hence remaining inaccessible for clinical practice. Also, its clinical relevance for cancer patients is still limited. Here, we develop a new method to quantify L1 activation, called RetroTest, based on targeted sequencing and a sophisticated bioinformatic pipeline, allowing its application in tumor biopsies. First, we performed the benchmarking of the method and confirmed its high specificity and reliability. Then, we unravel the L1 activation in HNSCC according to a more extensive cohort including all the HNSCC tumor stages. Our results confirm that RetroTest is remarkably efficient for L1 detection in tumor biopsies, reaching a high sensitivity and specificity. In addition, L1 retrotransposition estimation reveals a surprisingly early activation in HNSCC progression, contrary to its classical association with advanced tumor stages. This early activation together with the genomic mutational profiling of normal adjacent tissues supports field cancerization process in this tumor. These results underline the importance of estimating L1 retrotransposition in clinical practice towards an earlier and more efficient diagnosis in HNSCC. Highlights: RetroTest represents the first method to determine LINE-1 retrotransposition from tumor biopsies in real clinical settings. RetroTest not only offers global LINE-1 retrotransposition ratios but also identifies the active LINE-1 source elements. RetroTest elucidates a really early LINE-1 activation in early tumor stages of Head and Neck Squamous Cell Carcinoma. Whole Genome Analysis and LINE-1 retrotransposition demonstrates processes of field cancerization in Head and Neck Squamous Cell Carcinoma. LINE-1 retrotransposition favors an earlier and more efficient Head and Neck Squamous Cell Carcinoma diagnosis.

The relevant role of LINE‐1 (L1) retrotransposition in cancer has been recurrently demonstrated in recent years. However, the repetitive nature of retrotransposons makes their identification and detection inaccessible for clinical practice. Also, its clinical relevance for cancer patients is still limited. Here, we developed RetroTest, a new efficient method to quantify L1 activation based on targeted sequencing and a sophisticated bioinformatic pipeline, allowing its application in tumor biopsies. Firstly, we performed RetroTest benchmarking to confirm its high specificity and reliability. Then, we unraveled L1 activation in head‐and‐neck squamous cell carcinoma (HNSCC) according to an extensive patient cohort including all tumor stages. L1 retrotransposition estimation revealed a surprisingly early activation in HNSCC progression, contrary to its classical association with advanced stages. In addition, L1 activation together with genomic mutational profiling in normal adjacent tissues supported a field cancerization process, a phenomenon where a tissue develops multiple patches of cells with genetic and/or epigenetic alterations, increasing the risk of cancer development in that area. Overall, our results underline an early L1 activation in HNSCC and field characterization, raising L1 as a promising early diagnostic biomarker and supporting the importance of estimating L1 retrotransposition in clinical practice toward a more efficient diagnosis in HNSCC.