An Integrated Cancer Prevention Strategy: the Viewpoint of the Leon Berard Comprehensive Cancer Center Lyon, France.

This article describes some of the key prevention services in the Leon Berard Comprehensive Cancer Center (CLB) Lyon, France, which are based on clinical prevention services, outreach activities, and collaboration with professional and territorial health communities. In addition, research is embedded at all stages of the prevention continuum, from understanding cancer causes through to the implementation of prevention interventions during and after cancer. Health promotion activities in the community and dedicated outpatient primary cancer prevention services for individuals at increased risk have been implemented. The CLB's experience illustrates how prevention can be integrated into the comprehensive mission of cancer centers, and how in turn, the cancer centers may contribute to bridging the current fragmentation between cancer care and the different components of primary, secondary, and tertiary prevention. With increasing cancer incidence, the shift toward integrated prevention-centered cancer care is not only key for improving population health, but this may also provide a response to the shortage of hospital staff and overcrowding in cancer services, as well as offer opportunities to reduce carbon emissions from cancer care.

Added value of whole-exome and RNA sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel.

INTRODUCTION: The objective was to determine the added value of comprehensive molecular profile by whole-exome and RNA sequencing (WES/RNA-Seq) in advanced and refractory cancer patients who had no molecular-based treatment recommendation (MBTR) based on a more limited targeted gene panel (TGP) plus array-based comparative genomic hybridization (aCGH). MATERIALS AND METHODS: In this retrospective analysis, we selected 50 patients previously included in the PROFILER trial (NCT01774409) for which no MBT could be recommended based on a targeted 90-gene panel and aCGH. For each patient, the frozen tumor sample mirroring the FFPE sample used for TGP/aCGH analysis were processed for WES and RNA-Seq. Data from TGP/aCGH were reanalyzed, and together with WES/RNA-Seq, findings were simultaneously discussed at a new molecular tumor board (MTB). RESULTS: After exclusion of variants of unknown significance, a total of 167 somatic molecular alterations were identified in 50 patients (median: 3 [1-10]). Out of these 167 relevant molecular alterations, 51 (31%) were common to both TGP/aCGH and WES/RNA-Seq, 19 (11%) were identified by the TGP/aCGH only and 97 (58%) were identified by WES/RNA-Seq only, including two fusion transcripts in two patients. A MBTR was provided in 4/50 (8%) patients using the information from TGP/aCGH versus 9/50 (18%) patients using WES/RNA-Seq findings. Three patients had similar recommendations based on TGP/aCGH and WES/RNA-Seq. CONCLUSIONS: In advanced and refractory cancer patients in whom no MBTR was recommended from TGP/aCGH, WES/RNA-Seq allowed to identify more alterations which may in turn, in a limited fraction of patients, lead to new MBTR.

Uncovering immune checkpoint heterogeneity in oral squamous cell carcinoma using single cell RNA-sequencing data highlights three subgroups of patients with distinct immune phenotypes.

OBJECTIVES: In head and neck squamous cell carcinoma (HNSCC), PD-1/PD-L1 inhibitors remain inefficient in most patients, which points to the need for better characterization of immune checkpoint (ICP) molecule expression. MATERIAL AND METHODS: We evaluated the expression of 22 ICP ligands (ICPL) in 2,176 malignant cells from 10 patients in a public single-cell RNA-sequencing dataset and in two cohorts of HNSCC patients for which gene expression data are available. RESULTS: Based on ICPL expression, malignant cells formed three distinct clusters characterized either by a strong expression of ICPL together with an immune phenotype linked to IFN-γ response (cluster 1) or by a weak ICPL expression and little response to IFN-γ (clusters 2 and 3). Malignant cells from cluster 3 showed a high PD-L1 expression associated with NRF2 signature. The relevance of 3 groups of patients, i.e "high ICPL/high IFN-γ", "low ICPL/low IFN-γ" or "low ICPL/low IFN-γ/high PD-L1" was confirmed in a cohort of 259 OSCC whole tumor samples from TCGA and in the CLB-IHN cohort including patients treated with PD1/PD-L1 inhibitors. The heterogeneous expression of ICPL among patients' malignant cells was associated with immunologically distinct microenvironments, evaluated with the "hot/cold" and the Tumor microenvironment (TME) classification. Finally, the "low ICPL/low IFN-γ/high PD-L1" group 3 displayed a poor prognosis in the TCGA cohort. CONCLUSION: Hence, the global picture of ICPL gene expression in malignant cells from HNSCC patients may contribute to the broader issue of improving immunotherapy strategies though a better stratification of patients and the design of new treatment combinations.

GIInger predicts homologous recombination deficiency and patient response to PARPi treatment from shallow genomic profiles.

Homologous recombination deficiency (HRD) is a predictive biomarker for poly(ADP-ribose) polymerase 1 inhibitor (PARPi) sensitivity. Routine HRD testing relies on identifying BRCA mutations, but additional HRD-positive patients can be identified by measuring genomic instability (GI), a consequence of HRD. However, the cost and complexity of available solutions hamper GI testing. We introduce a deep learning framework, GIInger, that identifies GI from HRD-induced scarring observed in low-pass whole-genome sequencing data. GIInger seamlessly integrates into standard BRCA testing workflows and yields reproducible results concordant with a reference method in a multisite study of 327 ovarian cancer samples. Applied to a BRCA wild-type enriched subgroup of 195 PAOLA-1 clinical trial patients, GIInger identified HRD-positive patients who experienced significantly extended progression-free survival when treated with PARPi. GIInger is, therefore, a cost-effective and easy-to-implement method for accurately stratifying patients with ovarian cancer for first-line PARPi treatment.

A Radiomics Approach to Identify Immunologically Active Tumor in Patients with Head and Neck Squamous Cell Carcinomas.

BACKGROUND: We recently developed a gene-expression-based HOT score to identify the hot/cold phenotype of head and neck squamous cell carcinomas (HNSCCs), which is associated with the response to immunotherapy. Our goal was to determine whether radiomic profiling from computed tomography (CT) scans can distinguish hot and cold HNSCC. METHOD: We included 113 patients from The Cancer Genome Atlas (TCGA) and 20 patients from the Groupe Hospitalier Pitié-Salpêtrière (GHPS) with HNSCC, all with available pre-treatment CT scans. The hot/cold phenotype was computed for all patients using the HOT score. The IBEX software (version 4.11.9, accessed on 30 march 2020) was used to extract radiomic features from the delineated tumor region in both datasets, and the intraclass correlation coefficient (ICC) was computed to select robust features. Machine learning classifier models were trained and tested in the TCGA dataset and validated using the area under the receiver operator characteristic curve (AUC) in the GHPS cohort. RESULTS: A total of 144 radiomic features with an ICC >0.9 was selected. An XGBoost model including these selected features showed the best performance prediction of the hot/cold phenotype with AUC = 0.86 in the GHPS validation dataset. CONCLUSIONS AND RELEVANCE: We identified a relevant radiomic model to capture the overall hot/cold phenotype of HNSCC. This non-invasive approach could help with the identification of patients with HNSCC who may benefit from immunotherapy.

RSK3 switches cell fate: from stress-induced senescence to malignant progression.

BACKGROUND: TGFß induces several cell phenotypes including senescence, a stable cell cycle arrest accompanied by a secretory program, and epithelial-mesenchymal transition (EMT) in normal epithelial cells. During carcinogenesis cells lose the ability to undergo senescence in response to TGFß but they maintain an EMT, which can contribute to tumor progression. Our aim was to identify mechanisms promoting TGFß-induced senescence escape. METHODS: In vitro experiments were performed with primary human mammary epithelial cells (HMEC) immortalized by hTert. For kinase library screen and modulation of gene expression retroviral transduction was used. To characterize gene expression, RNA microarray with GSEA analysis and RT-qPCR were used. For protein level and localization, Western blot and immunofluorescence were performed. For senescence characterization crystal violet assay, Senescence Associated-ß-Galactosidase activity, EdU staining were conducted. To determine RSK3 partners FLAG-baited immunoprecipitation and mass spectrometry-based proteomic analyses were performed. Proteosome activity and proteasome enrichment assays were performed. To validate the role of RSK3 in human breast cancer, analysis of METABRIC database was performed. Murine intraductal xenografts using MCF10DCIS.com cells were carried out, with histological and immunofluorescence analysis of mouse tissue sections. RESULTS: A screen with active kinases in HMECs upon TGFß treatment identified that the serine threonine kinase RSK3, or RPS6KA2, a kinase mainly known to regulate cancer cell death including in breast cancer, reverted TGFß-induced senescence. Interestingly, RSK3 expression decreased in response to TGFß in a SMAD3-dependent manner, and its constitutive expression rescued SMAD3-induced senescence, indicating that a decrease in RSK3 itself contributes to TGFß-induced senescence. Using transcriptomic analyses and affinity purification coupled to mass spectrometry-based proteomics, we unveiled that RSK3 regulates senescence by inhibiting the NF-κΒ pathway through the decrease in proteasome-mediated IκBα degradation. Strikingly, senescent TGFß-treated HMECs display features of epithelial to mesenchymal transition (EMT) and during RSK3-induced senescence escaped HMECs conserve EMT features. Importantly, RSK3 expression is correlated with EMT and invasion, and inversely correlated with senescence and NF-κΒ in human claudin-low breast tumors and its expression enhances the formation of breast invasive tumors in the mouse mammary gland. CONCLUSIONS: We conclude that RSK3 switches cell fate from senescence to malignancy in response to TGFß signaling.

Spatial Transcriptomics Reveal Pitfalls and Opportunities for the Detection of Rare High-Plasticity Breast Cancer Subtypes.

Breast cancer is one of the most prominent types of cancers, in which therapeutic resistance is a major clinical concern. Specific subtypes, such as claudin-low and metaplastic breast carcinoma (MpBC), have been associated with high nongenetic plasticity, which can facilitate resistance. The similarities and differences between these orthogonal subtypes, identified by molecular and histopathological analyses, respectively, remain insufficiently characterized. Furthermore, adequate methods to identify high-plasticity tumors to better anticipate resistance are lacking. Here, we analyzed 11 triple-negative breast tumors, including 3 claudin-low and 4 MpBC, via high-resolution spatial transcriptomics. We combined pathological annotations and deconvolution approaches to precisely identify tumor spots, on which we performed signature enrichment, differential expression, and copy number analyses. We used The Cancer Genome Atlas and Cancer Cell Line Encyclopedia public databases for external validation of expression markers. By focusing our spatial transcriptomic analyses on tumor cells in MpBC samples, we bypassed the negative impact of stromal contamination and identified specific markers that are neither expressed in other breast cancer subtypes nor expressed in stromal cells. Three markers (BMPER, POPDC3, and SH3RF3) were validated in external expression databases encompassing bulk tumor material and stroma-free cell lines. We unveiled that existing bulk expression signatures of high-plasticity breast cancers are relevant in mesenchymal transdifferentiated compartments but can be hindered by abundant stromal cells in tumor samples, negatively impacting their clinical applicability. Spatial transcriptomic analyses constitute powerful tools to identify specific expression markers and could thus enhance diagnosis and clinical care of rare high-plasticity breast cancers.

An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers.

An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell­based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G2­M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00­6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care. SIGNIFICANCE: We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression.

Radiomics combined with transcriptomics to predict response to immunotherapy from patients treated with PD-1/PD-L1 inhibitors for advanced NSCLC.

Introduction: In this study, we aim to build radiomics and multiomics models based on transcriptomics and radiomics to predict the response from patients treated with the PD-L1 inhibitor. Materials and methods: One hundred and ninety-five patients treated with PD-1/PD-L1 inhibitors were included. For all patients, 342 radiomic features were extracted from pretreatment computed tomography scans. The training set was built with 110 patients treated at the Léon Bérard Cancer Center. An independent validation cohort was built with the 85 patients treated in Dijon. The two sets were dichotomized into two classes, patients with disease control and those considered non-responders, in order to predict the disease control at 3 months. Various models were trained with different feature selection methods, and different classifiers were evaluated to build the models. In a second exploratory step, we used transcriptomics to enrich the database and develop a multiomic signature of response to immunotherapy in a 54-patient subgroup. Finally, we considered the HOT/COLD status. We first trained a radiomic model to predict the HOT/COLD status and then prototyped a hybrid model integrating radiomics and the HOT/COLD status to predict the response to immunotherapy. Results: Radiomic signature for 3 months' progression-free survival (PFS) classification: The most predictive model had an area under the receiver operating characteristic curve (AUROC) of 0.94 on the training set and 0.65 on the external validation set. This model was obtained with the t-test selection method and with a support vector machine (SVM) classifier. Multiomic signature for PFS classification: The most predictive model had an AUROC of 0.95 on the training set and 0.99 on the validation set. Radiomic model to predict the HOT/COLD status: the most predictive model had an AUROC of 0.93 on the training set and 0.86 on the validation set. HOT/COLD radiomic hybrid model for PFS classification: the most predictive model had an AUROC of 0.93 on the training set and 0.90 on the validation set. Conclusion: In conclusion, radiomics could be used to predict the response to immunotherapy in non-small-cell lung cancer patients. The use of transcriptomics or the HOT/COLD status, together with radiomics, may improve the working of the prediction models.

Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas.

Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance: We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.

Occupational asbestos exposure and survival among lung cancer patients.

OBJECTIVE: This study investigated the association between occupational asbestos exposure (OAE) and survival in patients with histologically confirmed lung cancer (LC). METHODS: This monocentric study was conducted in the Comprehensive Cancer Centre Léon Bérard, Lyon, France. A systematic screening has been in place since 2014 for occupational exposure to carcinogens using a self-assessment questionnaire sent to all patients newly diagnosed with histologically confirmed LC identified through the multidisciplinary LC board from 2014 to 2019. When the physician suspected a work-related exposure from the questionnaire including job history, an occupational cancer consultation was carried out to detail carcinogen exposures and assess if the LC was work-related. Demographics, clinical characteristics and survival data were extracted from medical records. The association between asbestos exposure and overall survival (hazard ratio and 95% confidence intervals) was estimated by Cox proportional hazards regression. RESULTS: Overall, 702 patients were eligible to the present study, including 180 patients with OAE. In the crude analysis, LCs assessed as moderately or highly attributable to OAE were associated with decreased overall survival (HR = 1.32, 95 %CI 1.04-1.67) compared to LC without OAE or with a low degree of imputability to OAE (median follow-up 28.8 months). After adjustment for confounding (age at diagnosis, smoking status, stage, brain metastasis at diagnosis, and histology), the association of OAE with overall survival was no longer statistically significant (HR = 1.21, 95 %CI 0.94-1.56). CONCLUSION: Overall survival in occupationally asbestos exposed LC patients may be decreased in comparison with non-exposed LC patients, warranting further investigations in larger studies.

Intestinal Epithelial Cells Adapt to Chronic Inflammation through Partial Genetic Reprogramming.

Reactive oxygen species (ROS) are considered to be the main drivers of inflammatory bowel disease. We investigated whether this permanent insult compels intestinal stem cells to develop strategies to dampen the deleterious effects of ROS. As an adverse effect, this adaptation process may increase their tolerance to oncogenic insults and facilitate their neoplastic transformation. We submitted immortalized human colonic epithelial cells to either a mimic of chronic inflammation or to a chemical peroxide, analyzed how they adapted to stress, and addressed the biological relevance of these observations in databases. We demonstrated that cells adapt to chronic-inflammation-associated oxidative stress in vitro through a partial genetic reprogramming. Through a gene set enrichment analysis, we showed that this program is recurrently active in the intestinal mucosae of Crohn's and ulcerative colitis disease patients and evolves alongside disease progression. Based on a previously reported characterization of intestinal stem and precursor cells using tracing experiments, we lastly confirmed the activation of the program in intestinal precursor cells during murine colorectal cancer development. This adaptive process is thus likely to play a role in the progression of Crohn's and ulcerative disease, and potentially in the initiation of colorectal cancer.

Reliability of gene-expression profiling from tumor biopsy for refining neoadjuvant strategies in patients with head and neck squamous cell carcinoma.

While recent clinical trials evaluating neoadjuvant immune checkpoint inhibitors showed promising results in a subset of patients with head and neck squamous cell carcinomas (HNSCC), there is a need for the identification of robust biomarkers in tumor biopsies to improve patient selection. This context suggests unravelling transcriptomic heterogeneity between untreated paired samples from same patient with HNSCC. Based on previous studies and the analysis of publicly available gene expression profiles of paired tumor biopsies and surgical resection specimens, we discuss the reliability of tumor biopsy to capture the overall activation of targetable biological pathways in patients with HNSCC. Further studies investigating intratumor transcriptomic heterogeneity as well as the effect of sampling methods on gene expression are needed in patients with HNSCC, in order to develop innovative and relevant biomarker-driven neoadjuvant strategies.

Biomarkers of radioresistance in head and neck squamous cell carcinomas.

PURPOSE: Head and neck squamous cell carcinoma (HNSCC) is a major cause of morbidity and mortality. Although HNSCC is mainly caused by tobacco and alcohol consumption, infection by Human Papilloma Virus (HPV) has been also associated with the increasing incidence of oropharyngeal squamous cell carcinomas (OPSCC) during the past decades. HPV-positive HNSCC is characterized by a higher radiosensitivity compared to HPV-negative tumor. While several clinical trials are evaluating de-escaladed radiation doses strategies in HPV-positive HNSCC, molecular mechanisms associated with relative radioresistance in HPV-negative HNSCC are still broadly unknown. Our goal was to review recently proposed biomarkers of radioresistance in this setting, which may be useful for stratifying tumor's patient according to predicted level of radioresistance. CONCLUSIONS: most of biomarkers of radioresistance in HPV-negative HNSCC are identified using a hypothesis-driven approach, based on molecular mechanisms known to play a key role during carcinogenesis, compared to an unsupervised data-driven approach regardless the biological rational. DNA repair and hypoxia are the two most widely investigated biological and targetable pathways related to radioresistance in HNSCC. The better understanding of molecular mechanisms and biomarkers of radioresistance in HPV-negative HNSCC could help for the development of radiosensitization strategies, based on targetable biomarkers, in radioresistant tumors as well as de-escalation radiation dose strategies, based on biological level of radioresistance, in radiosensitive tumors.

Survival of bronchopulmonary cancers according to radon exposure.

Introduction: Residential exposure is estimated to be responsible for nearly 10% of lung cancers in 2015 in France, making it the second leading cause, after tobacco. The Auvergne-Rhône-Alpes region, in the southwest of France, is particularly affected by this exposure as 30% of the population lives in areas with medium or high radon potential. This study aimed to investigate the impact of radon exposure on the survival of lung cancer patients. Methods: In this single-center study, patients with a histologically confirmed diagnosis of lung cancer, and newly managed, were prospectively included between 2014 and 2020. Univariate and multivariate survival analyses were carried out using a non-proportional risk survival model to consider variations in risk over time. Results: A total of 1,477 patients were included in the analysis. In the multivariate analysis and after adjustment for covariates, radon exposure was not statistically associated with survival of bronchopulmonary cancers (HR = 0.82 [0.54-1.23], HR = 0.92 [0.72-1.18], HR = 0.95 [0.76-1.19] at 1, 3, and 5 years, respectively, for patients residing in category 2 municipalities; HR = 0.87 [0.66-1.16], HR = 0.92 [0.76-1.10], and HR = 0.89 [0.75-1.06] at 1, 3, and 5 years, respectively, for patients residing in category 3 municipalities). Discussion: Although radon exposure is known to increase the risk of lung cancer, in the present study, no significant association was found between radon exposure and survival of bronchopulmonary cancers.

Datasets for gene expression profiles of head and neck squamous cell carcinoma and lung cancer treated or not by PD1/PD-L1 inhibitors.

Identification of tumors harboring an overall active immune phenotype may help for selecting patients with advanced head and neck squamous cell carcinomas (HNSCC) and non-small cell lung cancer (NSCLC) who may benefit from immunotherapies. In this context, we generated targeted gene expression profiles in three and two independent cohorts of patients with HNSCC or NSCLC respectively, treated or not by PD-1/PD-L1 inhibitors. Notably, we generated two datasets including 102 and 82 patients with HNSCC or NSCLC treated with PD-1/PD-L1 inhibitors. Clinical information, including detailed survival raw data, is available for each patient, allowing to test association between gene expression data and patient survival (overall and progression-free survival). Moreover, we also generated gene expression datasets of 27 paired HNSCC samples from diagnostic biopsies and versus surgically resected specimens as well as 33 paired HNSCC samples at initial diagnosis (untreated) and at recurrence. Those datasets may allow to test the stability of a given biomarker across paired samples.

Immunologically active phenotype by gene expression profiling is associated with clinical benefit from PD-1/PD-L1 inhibitors in real-world head and neck and lung cancer patients.

INTRODUCTION: Identification of tumours harbouring an overall active immune phenotype may help for selecting patients with advanced head and neck squamous cell carcinomas (HNSCC) and non-small cell lung cancer (NSCLC) who may benefit from immunotherapies. Our objective was to develop a reliable and stable scoring system to identify those immunologically active tumours. METHODS: Using gene expression profiles of 421 HNSCC, we developed a score to identify immunologically active tumours. Validation of the 'HOT' score was done in 40 HNSCC and 992 NSCLC. Stability of the 'HOT' score was tested in paired HNSCC samples from diagnostic biopsies versus surgically resected specimens, untreated versus recurrent samples, and pre-versus post-cetuximab samples in a total of 76 patients. The association between the 'HOT' score with overall survival (OS) and progression-free survival (PFS) was tested in 184 patients with HNSCC or NSCLC treated with PD-1/PD-L1 inhibitors. RESULTS: A 27-gene expression based 'HOT' score was correlated with: (i) PD-L1 and IDO1 expression, (ii) TCD8 infiltrate and (iii) activation of the IFN-γ pathway. The HOT score concordance when comparing diagnostic biopsies and surgically resected specimens was higher than in untreated samples versus recurrent or pre-versus post-cetuximab samples. In 102 and 82 patients with HNSCC or NSCLC treated with PD-1/PD-L1 inhibitors, the HOT score was associated with an improved OS and PFS in multivariate analysis. CONCLUSION: The 'HOT' score is a simple and robust approach to identify real-world patients with HNSCC and NSCLC immunologically active tumours who may benefit from PD-1/PD-L1 inhibitors.