A patient with a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic non-small cell lung cancer (NSCLC) experienced a multisite radiological progression at 3 months after initiation of chemoimmunotherapy as first-line treatment for metastatic disease. After the radiological progression, while she was not undergoing treatment, the patient had spontaneous lesions shrinkage and further achieved a prolonged complete response. Genomic and transcriptomic data collected at baseline and at the time of pseudoprogression allowed us to biologically characterize this rare response pattern. We observed the presence of a tumor-specific T-cell response against tumor-specific neoantigens (TNAs). Endogenous retroviruses (ERVs) expression following chemoimmunotherapy was also observed, concurrent with biological features of an anti-viral-like innate immune response with type I IFN signaling and production of CXCR3-associated chemokines. This is the first biological characterization of a NSCLC pseudoprogression under chemoimmunotherapy followed by a prolonged complete response in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated NSCLC. These clinical and biological data underline that even patients with multiple factors of resistance to immune checkpoint inhibitors could trigger a tumor-specific immune response to tumor neoantigen, leading to complete eradication of the tumor and probably a vaccinal immune response.

BackgroundT-cell immune infiltrates are robust prognostic variables in localised colon cancer. Evaluation of prognosis using artificial intelligence is an emerging field. We evaluated whether machine learning analysis improved prediction of patient outcome in comparison with analysis of T cell infiltrate only or in association with clinical variables.MethodsWe used data from two phase III clinical trials (Prodige-13 and PETACC08) and one retrospective Italian cohort (HARMONY). Cohorts were split into training (N = 692), internal validation (N = 297) and external validation (N = 672) sets. Tumour slides were stained with CD3mAb. CD3 Machine Learning (CD3ML) score was computed using graphical parameters within the tumour tiles obtained from CD3 slides. CD3 infiltrates in tumour core and invasive margin were automatically detected. Associations of CD3 infiltrates and CD3ML with 5-year Disease-Free Survival (DFS) were examined using univariate and multivariable survival models by Cox regression.FindingsCD3 density both in the invasive margin and the tumour core were significantly associated with DFS in the different sets. Similarly, CD3ML score was significantly associated with DFS in all sets. CD3 assessment did not provide added value on top of CD3ML assessment (Likelihood Ratio Test (LRT), p = 0.13). In contrast, CD3ML improved prediction of DFS when combined with a clinical risk stage (LRT, p = 0.001). Stratified by clinical risk score (High or Low), patients with low CD3ML score had better DFS.InterpretationIn all tested sets, machine learning analysis of tumour cells improved prediction of prognosis compared to clinical parameters. Adding tumour-infiltrating lymphocytes assessment did not improve prognostic determination.FundingThis research received no external funding.

Immune checkpoint inhibitors (ICIs) have improved the care of patients in multiple cancer types. However, PD-L1 status, high Tumor Mutational Burden (TMB), and mismatch repair deficiency are the only validated biomarkers of efficacy for ICIs. These markers remain imperfect, and new predictive markers represent an unmet medical need. Whole-exome sequencing was carried out on 154 metastatic or locally advanced cancers from different tumor types treated by immunotherapy. Clinical and genomic features were investigated using Cox regression models to explore their capacity to predict progression-free survival (PFS). The cohort was split into training and validation sets to assess validity of observations. Two predictive models were estimated using clinical and exome-derived variables, respectively. Stage at diagnosis, surgery before immunotherapy, number of lines before immunotherapy, pleuroperitoneal, bone or lung metastasis, and immune-related toxicity were selected to generate a clinical score. KRAS mutations, TMB, TCR clonality, and Shannon entropy were retained to generate an exome-derived score. The addition of the exome-derived score improved the prediction of prognosis compared with the clinical score alone. Exome-derived variables could be used to predict responses to ICI independently of tumor type and might be of value in improving patient selection for ICI therapy.

NLRP3 is a pattern recognition receptor with a well-documented role in inducing inflammasome assembly in response to cellular stress. Deregulation of its activity leads to many inflammatory disorders including gouty arthritis, Alzheimer disease, and cancer. Whereas its role in the context of cancer has been mostly explored in the immune compartment, whether NLRP3 exerts functions unrelated to immunity in cancer development remains unexplored. Here, we demonstrate that NLRP3 interacts with the ATM kinase to control the activation of the DNA damage response, independently of its inflammasome activity. NLRP3 down-regulation in both broncho- and mammary human epithelial cells significantly impairs ATM pathway activation, leading to lower p53 activation, and provides cells with the ability to resist apoptosis induced by acute genotoxic stress. Interestingly, NLRP3 expression is down-regulated in non-small cell lung cancers and breast cancers, and its expression positively correlates with patient overall survival. Our findings identify a novel non-immune function for NLRP3 in maintaining genome integrity and strengthen the concept of a functional link between innate immunity and DNA damage sensing pathways to maintain cell integrity.

A novel crosstalk between immunogenic and oncometabolic pathways triggered by T cell-released interferon-gamma (IFN-ɣ) has been recently identified. This IFN-ɣ-pyruvate kinase M2-β-catenin axis relies on fibroblast growth factor 2 (FGF2) signaling in tumor cells and leads to hyperprogressive disease on immune checkpoint blockade (ICB) in preclinical models. This result underlines how IFN-ɣ signaling may have distinct effects on tumor cells depending on their oncogenic and metabolic features. On the basis of these data, this study aims to explore the relationship between genomic tumor FGF2 or FGF/FGF receptor (FGFR) amplification and immunotherapy response in patients with metastatic solid cancers. We used a large genomic data set of 545 ICB-treated patients and compared outcomes between those with and without FGF2 genomic amplification. Patients with no FGF2 genomic amplification had significantly longer progression-free survival (PFS) (HR=0.55 (95% CI 0.4, 0.8); p value=0.005) and overall survival (OS) (HR=0.56 (0.3, 0.9); p value=0.02) than patients harboring an FGF2 amplification. We next questioned whether such an observation may extend to genomic amplification of the FGF/FGFR pathway. Similarly, patients with no FGF/FGFR genomic amplification had longer PFS (HR=0.71 (0.8, 0.9), p value=0.004) and OS (HR=0.77 (0.6, 1); p value=0.06). RNA sequencing analysis of tumors between the amplified and non-amplified populations showed distinct expression profiles concerning oncogenic pathways. Importantly, using a cohort of patients untreated with ICB from the The Cancer Genome Atlas, we show that FGF2 and FGF/FGFR genomic amplification were not associated with prognosis, thus demonstrating that we identified a predictive biomarker of immunotherapy resistance.

Background/Aim: Bevacizumab and chemotherapy are used in glioblastoma multiforme (GBM) relapse. However, the choice of chemotherapeutic agent remains an open question and this study aimed to evaluate the efficacy and safety of different combinations. Patients and Methods: Between June 2005 and August 2020, all patients treated with chemotherapy plus bevacizumab (BVZ) for recurrent glioblastoma in the Georges-François Leclerc Cancer Center, Dijon, France were included in this retrospective comparative study. The primary objective was progression-free survival (PFS) and as secondary objectives, overall survival (OS), disease control rate (DCR), and safety were investigated. Factors associated with response were also analyzed. Results: A total of 160 patients were screened: 100 received fotemustine plus BVZ (62%) and 62 (38%) received another cytotoxic agent plus BVZ: 35 (22%) irinotecan (IRI), 18 (11%) temozolomide (TEM), and 7 (4%) lomustine (LOM). In the whole population, median PFS was 4.47 months, median OS was 9 months, and 3-month DCR was 51%. Regarding survival according to treatment, median OS was significantly lower in the fotemustine group compared to that in other cytotoxic agents: 7.3 vs. 19.9 months. In the fotemustine group, steroids use at baseline and low Karnofsky performance status were associated with poor median OS. Grade 3-4 adverse events were found in 21.9%, with no difference between groups, but 7 patients had grade 5 adverse events in the fotemustine group. Conclusion: Using real-life data, this study showed lower efficacy of fotemustine and bevacizumab, as compared to IRI or TEM or LOM-BVZ combinations.

Plasmacytoid dendritic cells (pDCs) represent a subset of antigen-presenting cells that play an ambivalent role in cancer immunity. Here, we investigated the clinical significance of circulating pDCs and their interaction with tumor-specific T cell responses in patients with non-small cell lung cancer (NSCLC, n = 126) . The relation between intratumoral pDC signature and immune checkpoint inhibitors efficacy was also evaluated. Patients with NSCLC had low level but activated phenotype pDC compared to healthy donors. In overall population, patients with high level of pDC (pDC(high)) had improved overall survival (OS) compared to patients with pDC(low), median OS 30.4 versus 20.7 months (P = 0.013). This clinical benefit was only observed in stage I to III patients, but not in metastatic disease. We showed that patients harboring pDC(high) profile had high amount of Th1-diffentiation cytokine interleukin-12 (IL-12) in blood and had functional T cells directed against a broad range of tumor antigens. Furthermore, a high pDC signature in the tumor microenvironment was associated with improved clinical outcome in patients treated with anti-PD-(L)1 therapy. Overall, this study showed that circulating pDC(high) is associated with long-term OS in NSCLC and highlighted the predictive value of intratumor pDC signature in the efficacy of immune checkpoint inhibitors.

Background Endogenous retroviruses (ERVs) are highly expressed in various cancer types and are associated with increased innate immune response and better efficacy of antiprogrammed death-1/ligand-1 (anti-PD1/PD-L1)-directed immune checkpoint inhibitors (ICI) in preclinical models. However, their role in human non-small cell lung cancer (NSCLC) remains unknown. Methods We conducted a retrospective study of patients receiving ICI for advanced NSCLC in two independent cohorts. ERV expression was determined by RNA sequencing. The primary endpoint was progression-free survival (PFS) under ICI. The secondary endpoint was overall survival (OS) from ICI initiation. We studied expression of 6205 ERVs. Multivariate Cox regression model with lasso penalty was estimated on the training set to select ERVs significantly associated with survival. The predictive power of these ERVs was compared with that of previously described transcriptomic signatures. Results We studied two independent cohorts of 89 and 70 patients, used as training and validation sets. Clinicopathological characteristics included 75% of patients with non-squamous NSCLC. We selected four ERVs significantly associated with PFS. Only high MER4 ERV was associated with better PFS and OS in both cohorts. From a biological point of view, high MER4 expression is associated with higher infiltration of eosinophils and inflammatory gene signatures, while low MER4 expression is associated with enrichment in metabolism and proliferation signatures. Adding MER4 to previously described transcriptomic signatures of response to ICI improved their predictive power. Conclusions MER4 ERV expression is useful to stratify risk and predict PFS and OS in patients treated with ICI for NSCLC. It also improves the predictive power of other known transcriptomic signatures.

Metastatic breast cancer (MBC) is frequently managed by platinum-based chemotherapy during the disease course. The real benefit of these treatments is uncertain at advanced stages of the disease and in non-triple-negative subtypes. Since homologous recombination deficiency (HRD) could inform about tumor sensitivity to DNA-damaging agents, we aimed to determine biomarkers of genomic instability, and their link with platinum efficacy. In this single-center study, we report BRCA1/2 mutational status, HRD score and signature 3 levels, all obtained by tumor exome sequencing, in 86 patients with various subtypes of MBC and who received platinum-based chemotherapy. Overall response rate, disease control rate, PFS and PFS2/PFS1 ratio were evaluated to assess platinum-based chemotherapy efficacy. Among the 86 tumor samples analyzed, 7 harbored BRCA1/2 mutations. We found a subset of BRCA-proficient MBC with high HRD score or high S3 levels, comparable to BRCA-mutated tumors. However, these patients with high HRD score or high S3 tumor level do not seem to benefit more from platinum-based chemotherapy than the others, in terms of response rates and/or PFS, regardless of BC molecular subtype. By multivariate analysis, only the absence of liver metastases was independently associated with significantly better PFS on platinum-based chemotherapy. However, some of our exploratory analyses reveal that certain methods, when optimized, seem to associate with platinum benefit. Tumor exome sequencing methodology for quantifying HRD has to be approached systematically, and further validated and standardized prior to its clinical use. Further studies are warranted to confirm these results to guide platinum use in MBC.

Notre équipe a pu établir en 2020 à partir de la cohorte PETTAC08 un score digital baptisé DGMate pour DiGital tuMor pArameTErs [1] estimant le pronostic et le risque de rechute des malades atteints de cancer du côlon avec atteintes ganglionnaires (stade III). Ce score est établi à partir d'une lame de pathologie marquée en immunohistochimie par l'anticorps CD3. Grâce à un modèle d'intelligence artificielle nommé ColoClass, la zone tumorale est automatiquement détectée puis 8 paramètres de couleurs et de textures sont extraits de la tumeur pour estimer le DGMate. Nous avons cherché à savoir si ce score pouvait s'avérer pronostique dans d'autres cohortes de cancers de côlon. Nous avons étudié de manière rétrospective les cohortes suivantes : PRODIGE 13 (1088 patients dont 524 stade II et 564 stade III), le Registre Bourguignon des Cancers Digestifs (127 patients dont 62 stade II et 65 stade III) et PETACC08 (173 patients de stade III). Les lames ont été marquées par l'anticorps CD3 (clone F7.2.38) puis numérisées avant d'être analysées par ColoClass. Le DGMate a ensuite été estimé pour chaque lame. Le DGmate s'est montré pronostique dans les trois cohortes étudiées pour les patients atteints d'un cancer du côlon de stade III confirmant les résultats obtenus sur la cohorte PETACC08. En revanche le DGMate perd sa valeur pronostique pour les patients atteints d'un cancer de stade II soulignant la nécessité d'estimer un score digital spécifique pour ces malades. Notre score digital permet d'établir un pronostic et un risque de rechute des malades atteints d'un cancer du côlon de stade III. Nous devons à présent travailler sur sa standardisation de manière à pouvoir utiliser le DGMate de manière prospective.

Monoclonal antibodies targeting PD1/PD-L1 are game changers in advanced non-small cell lung cancer (NSCLC), but biomarkers are lacking. We previously reported the prognostic role of splenic volume in digestive cancer and its correlation with the presence of immunosuppressive cells. The aim of this study was to evaluate the prognostic role of splenic volume in NSCLC patients treated with immune checkpoint inhibitors (ICIs). We conducted a retrospective study of 276 patients receiving ICIs for advanced NSCLC in the Georges François Leclerc Cancer Center. The association between splenic volume at baseline and at two months of therapy and progression-free survival (PFS) during ICI treatment or overall survival (OS) from ICI initiation was evaluated using univariate and multivariable Cox analyses. Splenic volume during treatment and the change in splenic volume were associated with poor PFS (respectively p = 0.02 and p = 0.001) and with OS (respectively p < 1.10−3 and p < 1.10−3). Baseline splenic volume at the first evaluation was also associated with poor OS (p = 0.001). LDH rate and dNLR were positively correlated with splenic volume, as well as with its evolution. After the adjustment of clinical variables, splenic volumes remained a predictive marker of immunotherapy efficacy. Splenic volume is a prognostic biomarker in patients with advanced NSCLC treated with ICIs.

Anti-PD1/PD-L1-directed immune checkpoint inhibitors are game changers in advanced non-small-cell lung cancer, but biomarkers are lacking. The aim of our study was to find clinically relevant biomarkers of the efficacy of ICI in non-squamous NSCLC. We conducted a retrospective study of patients receiving ICI for advanced non squamous NSCLC in two cohorts. For a subset of patients, RNAseq data were generated on tumor biopsy taken before ICI. The primary end point was progression-free survival under ICI. Secondary end point was overall survival from ICI initiation. In the cohort, we studied 231 patients. Clinico-pathological characteristics included KRAS mutant status (n = 88), TTF1-positive expression (n = 136), LIPI (Lung Immune Prognostic Index) score of 0 (n = 116). In our cohort, lack of TTF1 expression, LIPI score >0, line of treatment >1, and liver metastases were associated with poorer PFS. TTF1 and PD-L1 status could be used to stratify survival and improve the AUC for prediction of prognosis in comparison with the PD-L1 gold standard. Using an external cohort of 154 patients, we confirmed the independent prognostic role of TTF1. TTF1 expression and PD-L1 can be used to stratify risk and predict PFS and OS in patients treated with ICI for NS-NSCLC.

PURPOSE:The first line treatment of advanced pancreatic ductal adenocarcinoma cancer (PDAC) comprises a FOLFIRINOX regimen for most patients with good performance status. However, no biomarker to predict efficacy is currently available. We investigated whether exome sequencing could be used to predict progression-free and overall survival in patients undergoing FOLFIRINOX for PDAC.METHODS:In this single-center observational study, we included 78 patients with advanced PDAC who underwent somatic and germline exome analyses during first line therapy with FOLFIRINOX or gemcitabine. Exome-derived variables associated with outcome were then used in Cox regression models to generate a composite biomarker.RESULTS:Performance status, tumor stage, liver metastasis, and lung metastasis were retained to generate a prognostic clinical score associated with overall and progression-free survival. Clonality, ploidy, and copy number variant (CNV) signatures 1 and 5, as well as gene variants in the calcium, non-homologous end-joining (NHEJ), and spliceosome pathways, were retained to generate a genomic prognostic score. The addition of genomic score improved the prediction of prognosis compared to the clinical score alone.CONCLUSIONS:This study underlines that structural and pathway genomic features could be used to predict FOLFIRINOX survival in patients with advanced PDAC.

PURPOSE:Immune infiltration is a prognostic factor in high-grade serous ovarian carcinoma (HGSC) but immunotherapy efficacy is disappointing. Genomic instability is now used to guide the therapeutic value of PARP inhibitors. We aimed to investigate exome-derived parameters to assess the tumor microenvironment according to genomic instability profile.METHODS:We used the HGSC TCGA (the cancer genome atlas) dataset with genomic characteristics, including homologous recombination deficiency (HRD), copy number variant (CNV) signatures, TCR (T cell receptor) clonality and abundance of tissue-infiltrating immune and stromal cell populations. We then investigated the relationship with survival data.RESULTS:In 578 HGSC patients, HRD status, CNV signature 7 and TCR clonality were associated with longer survival. The combination of high CNV signature 7 expression and HRD status or high CNV signature 3 expression and high TCR clonality was associated with a trend towards longer survival compared to each variable alone. Combining T cell infiltrate and TCR clonality improved the prognostic value compared to T cells infiltration alone. Prognostic value of TCR clonality was confirmed in an independent cohort.CONCLUSIONS:TCR clonality is an emerging prognostic biomarker that improves T cell infiltrate information. Analysis of TCR clonality combined with genomic instability could be an interesting prognostic biomarker.