Lung cancer is the most common cause of cancer mortality worldwide, and non-small cell lung cancer (NSCLC) represents 80% of lung cancer subtypes. Patients with localized non-small cell lung cancer may be considered for upfront surgical treatment. However, the overall 5-year survival rate is 59%. To improve survival, adjuvant chemotherapy (ACT) was largely explored and showed an overall benefit of survival at 5 years < 7%. The evaluation of recurrence risk and subsequent need for ACT is only based on tumor stage (TNM classification); however, more than 25% of patients with stage IA/B tumors will relapse. Recently, adjuvant targeted therapy has been approved for EGFR-mutated resected NSCLC and trials are evaluating other targeted therapies and immunotherapies in adjuvant settings. Costs, treatment duration, emergence of resistant clones and side effects stress the need for a better selection of patients. The identification and validation of prognostic and theranostic markers to better stratify patients who could benefit from adjuvant therapies are needed. In this review, we report current validated clinical, pathological and molecular prognosis biomarkers that influence outcome in resected NSCLC, and we also describe molecular biomarkers under evaluation that could be available in daily practice to drive ACT in resected NSCLC.

A large interindividual variability has been observed in anti Programmed cell Death 1 (anti-PD1) therapies efficacy. The aim of this study is to assess the correlation of soluble PD-1 (sPD-1), soluble Programmed cell Death Ligand 1 (sPD-L1), Vascular Endothelial Growth Factor A (VEGFA), soluble CD40 ligand (sCD40L) and soluble CD44 (sCD44), with survival in nivolumab-treated metastatic non-small cell lung cancer (NSCLC) patients. Plasma biomarkers were assayed at baseline and after two cycles of nivolumab. A cut-off of positivity for sPD-1, sPD-L1 and sCD40L expressions was defined as a plasma level above the lower limit of quantification. Baseline sPD-1 and sPD-L1 levels were subsequently analyzed in a control group of EGFR-mutated (Epidermal Growth Factor Receptor) NSCLC patients. Association between survival and biomarkers was investigated using Cox proportional hazard regression model. Eighty-seven patients were included (51 nivolumab-treated patients, 36 in EGFR-mutated group). In nivolumab group, baseline sPD-1, sPD-L1 and sCD40L were positive for 15(29.4%), 27(52.9%) and 18(50%) patients, respectively. We defined a composite criteria (sCombo) corresponding to sPD-1 and/or sPD-L1 positivity for each patient. In nivolumab group, baseline sCombo positivity was associated with shorter median progression-free survival (PFS) (78 days 95%CI (55–109) vs. 658 days (222-not reached); HR: 4.12 (1.95–8.71), p = 0.0002) and OS (HR: 3.99(1.63–9.80), p = 0.003). In multivariate analysis, baseline sCombo independently correlated with PFS (HR: 2.66 (1.17–6.08), p = 0.02) but not OS. In EGFR-mutated group, all patients were baseline sCombo positive; therefore this factor was not associated with survival. After two cycles of nivolumab, an increased or stable sPD-1 level independently correlated with longer PFS (HR: 0.49, 95%CI (0.30–0.80), p = 0.004) and OS (HR: 0.39, 95%CI (0.21–0.71), p = 0.002). VEGFA, sCD40L and sCD44 did not correlate with survival. We propose a composite biomarker using sPD-1and sPDL-1 to predict nivolumab efficacy in NSCLC patients. A larger validation study is warranted.

Immune checkpoint inhibitors (ICIs) have demonstrated to be highly efficient in treating solid tumors; however, many patients have limited benefits in terms of response and survival. This rapidly led to the investigation of combination therapies to enhance response rates. Moreover, predictive biomarkers were assessed to better select patients. Although PD-L1 expression remains the only validated marker in clinics, molecular profiling has brought valuable information, showing that the tumor mutation load and microsatellite instability (MSI) status were associated to higher response rates in nearly all cancer types. Moreover, in lung cancer, EGFR and MET mutations, oncogene fusions or STK11 inactivating mutations were associated with low response rates. Cancer progression towards invasive phenotypes that impede immune surveillance relies on complex regulatory networks and cell interactions within the tumor microenvironment. Epigenetic modifications, such as the alteration of histone patterns, chromatin structure, DNA methylation status at specific promoters and changes in microRNA levels, may alter the cell phenotype and reshape the tumor microenvironment, allowing cells to grow and escape from immune surveillance. The objective of this review is to make an update on the identified epigenetic changes that target immune surveillance and, ultimately, ICI responses, such as histone marks, DNA methylation and miR signatures. Translational studies or clinical trials, when available, and potential epigenetic biomarkers will be discussed as perspectives in the context of combination treatment strategies to enhance ICI responses in patients with solid tumors.

Immunotherapy represents one of the most promising therapeutic approaches in lung cancer, however 50% of lung cancer patients will not respond to this treatment, while others will have transitory or durable responses. Because side effects may be life threatening and treatment costs remain very high, the identification of predictive markers is mandatory and actually extensively studied. Factors that determine response to immune checkpoint inhibitors (ICI) are numerous including tumor microenvironment, immune tumor infiltrates, expression of immune checkpoint proteins (PD-1/PD-L1), gene expression signatures and molecular tumor profiles. Based on high impact factor publications and recent literature this review focuses on the potential predictive value of tumor molecular alterations and tumor mutation burden as predictive markers of response or resistance to ICI. We also discuss the role of circulating tumor DNA (ctDNA) to monitor ICI responses and propose an algorithm that integrates molecular markers upcoming recommendations for first line treatment.

Recent changes in lung cancer care, including new approvals in first line and the introduction of high-throughput molecular technologies in routine testing led us to question ourselves on how deeper molecular testing may be helpful for the optimal use of targeted drugs. In this article, we review recent results in the scope of personalized medicine in lung cancer. We discuss biomarkers that have a therapeutic predictive value in lung cancer with a focus on recent changes and on the clinical value of large scale sequencing strategies. We review the use of second- and third-generation EGFR and ALK inhibitors with a focus on secondary resistance alterations. We discuss anti-BRAF and anti-MEK combo, emerging biomarkers as NRG1 and NTRKs fusions and immunotherapy. Finally, we discuss the different technical issues of comprehensive molecular profiling and show how large screenings might refine the prediction value of individual markers. Based on a review of recent publications (2012–2018), we address promising approaches for the treatment of patients with lung cancers and the technical challenges associated with the identification of new predictive markers.

Background: A high density of resident memory T cells (T_RM) in tumors correlates with improved clinical outcomes in immunotherapy-treated patients. In most clinical studies, T_RM are defined by the CD103 marker. However, it is clearly established that not all T_RM express CD103, but can be defined by other markers (CD49a, CD69, etc). The frequency of these subpopulations of T_RM expressing or not CD103 varies according to the location of the cancer. Little is known about their functionality and their predictive impact on response to immunotherapy. In preclinical models, only some subpopulations of T_RM are associated with cancer vaccine efficacy. Methods: Multiparametric cytometry analyses were used to demonstrate the presence of T_RM subpopulations in the lung in mice after vaccination and in fresh ex vivo human non-small cell lung cancer (NSCLC). An analysis of the T-cell repertoire of these T_RM was conducted to search for their relationships. Multiplex immunofluorescence techniques were used to quantify intratumor infiltration of T_RM subpopulations in two cohorts of patients with NSCLC. The impact on the clinical outcome of the T_RM tumor infiltration was also investigated. Results: We identified two main T_RM subpopulations in tumor-infiltrating lymphocytes derived from patients with NSCLC: one co-expressing CD103 and CD49a (double positive (DP)), and the other expressing only CD49a (simple positive (SP)); both exhibiting additional T_RM surface markers like CD69. Despite higher expression of inhibitory receptors, DP T_RM exhibited greater functionality compared with SP T_RM. Analysis of T-cell receptor (TCR) repertoire and expression of the stemness marker TCF1 revealed shared TCRs between populations, with the SP subset appearing more progenitor-like phenotype. In the training cohort, PD-L1 (Programmed Death-Ligand 1) and TCF1⁺CD8⁺T cells predict response to anti-PD-1. In patient with NSCLC validation cohorts, only DP T_RM predicted PD-1 blockade response. Multivariate analysis, including various biomarkers associated with responses to anti-PD-(L)1, such as total CD8, TCF1⁺CD8⁺T cells, and PD-L1, showed that only intratumoral infiltration by DP T_RM remained significant. Conclusions: This study highlights the non-equivalence of T_RM subpopulations. The population of T_RM co-expressing CD103 and CD49a appears to be the most functional and has the most significant capacity for predicting response to immunotherapy in multivariate analysis in patients with NSCLC.