Efficacy of Pembrolizumab vs. Nivolumab Plus Ipilimumab in Metastatic NSCLC in Relation to PD-L1 and TMB Status

The efficacy of immune checkpoint inhibitor (ICI) therapy concerning programmed death ligand 1 (PD-L1) status is well established in patients diagnosed with non-small cell lung cancer (NSCLC). However, there remains a paucity of evidence regarding the efficacy concerning tumor mutational burden (TMB) in both clinical trials and real-world data (RWD). In the current article, clinicopathological and molecular epidemiological data were meticulously collected, and treatment modalities were meticulously recorded. The final analysis included a study population of 194 patients. Median age was 67 years (range 37-86), with the majority being male (71.13%), and 85.71% of patients were either current or former smokers at diagnosis. Adenocarcinoma accounted for most diagnoses (71.65%), followed by squamous cell carcinoma (24.23%). In terms of PD-L1 status, 42.78% had an expression level below 1%, 28.35% had an expression between 1-49%, and 28.87% had an expression above 50%. The TMB ranged from 0 to 75, with a median of 10.31 (range 0-75) for PD-L1 expression below 1%, with a median of 9.73 (range 0.95-39.63) for PD-L1 expression between 1-49%, and a median of 9.72 (range 0.95-48) for PD-L1 expression above 50%. Corresponding to patients with low PDL-1 less than 1% and low TMB (0-5), the median overall survival (mOS) was 16 (p = 0.18), and 15 months (p = 0.22), patients with medium PDL-1 (1-49%) and medium TMB (5-10), the mOS was 15 (p = 0.18) and 16 months (p = 0.22), patients with high PDL-1 (>50) and high TMB (>10), the mOS was 24 (p = 0.18) and 21 (p = 0.22) months. This study represents the largest academic RWD dataset concerning PD-L1 and TMB status in patients with locally advanced and metastatic NSCLC.

Durvalumab ± Tremelimumab + Platinum-Etoposide in Extensive-Stage Small Cell Lung Cancer (CASPIAN): Outcomes by PD-L1 Expression and Tissue Tumor Mutational Burden

PURPOSE

In the CASPIAN trial, first-line durvalumab plus platinum-etoposide (EP) significantly improved overall survival (OS) versus EP alone in extensive-stage small cell lung cancer (ES-SCLC). We report exploratory analyses of CASPIAN outcomes by programmed cell death ligand-1 (PD-L1) expression and tissue tumor mutational burden (tTMB).

EXPERIMENTAL DESIGN

Patients were randomized (1:1:1) to durvalumab (1,500 mg) plus EP, durvalumab plus tremelimumab (75 mg) plus EP, or EP alone. Treatment effects in PD-L1 and tTMB subgroups were estimated using an unstratified Cox proportional hazards model.

RESULTS

The PD-L1 and tTMB biomarker-evaluable populations (BEP) comprised 54.4% (438/805) and 35.2% (283/805) of the intention-to-treat population, respectively. PD-L1 prevalence was low: 5.7%, 25.8%, and 28.3% had PD-L1 expression on ≥1% tumor cells (TC), ≥1% immune cells (IC), and ≥1% TCs or ICs, respectively. OS benefit with durvalumab plus EP versus EP was similar across PD-L1 subgroups, with HRs all falling within the 95% confidence interval (CI) for the PD-L1 BEP (0.47‒0.79). OS benefit with durvalumab plus tremelimumab plus EP versus EP was greater in PD-L1 ≥1% versus <1% subgroups, although CIs overlapped. There was no evidence of an interaction between tTMB and treatment effect on OS (durvalumab plus EP vs. EP, P = 0.916; durvalumab plus tremelimumab plus EP vs. EP, P = 0.672).

CONCLUSIONS

OS benefit with first-line durvalumab plus EP in patients with ES-SCLC was observed regardless of PD-L1 or tTMB status. PD-L1 expression may prove to be a useful biomarker for combined treatment with PD-(L)1 and CTLA-4 inhibition, although this requires confirmation with an independent dataset. See related commentary by Rolfo and Russo, p. 652.

Biomarkers of immunotherapy for non-small cell lung cancer

Immunotherapy is revolutionizing the treatment of non-small cell lung cancer by targeting immune checkpoint proteins, including programmed death-1, programmed death ligand 1 and cytotoxic T-lymphocyte-associated antigen 4. Several immune checkpoint inhibitors, including programmed death ligand 1 inhibitors, programmed death-1 inhibitors and cytotoxic T-lymphocyte-associated antigen 4 inhibitors, were approved for the treatment of patients with advanced non-small cell lung cancer. Programmed death ligand 1 expression is currently the only predictive biomarker for immune checkpoint inhibitors to guide the treatment strategy in these patients. However, programmed death ligand 1 expression is not a perfect biomarker for predicting the efficacy of immunotherapy. Therefore, various biomarkers such as tumour mutation burden, tumour microenvironment, gut microbiome and T-cell receptor repertoire have been proposed to predict the efficacy of immunotherapy more accurately. Additionally, combining different biomarkers may provide a more accurate prediction of response to immunotherapy. This article reports the review of the latest evidence of the predictive marker of immunotherapy in patients with advanced non-small cell lung cancer.

Biomarkers for Immunotherapy in Driver-Gene-Negative Advanced NSCLC

Outcome improvement in patients with driver-gene-negative advanced non-small cell lung cancer (NSCLC) has been significantly enhanced through targeting the immune system, specifically the PD-L1/PD-1 axis. Nevertheless, only a subset of patients with advanced NSCLC may derive benefits from immuno-monotherapy or immunotherapy combined with chemotherapy. Hence, in order to identify patients who will gain the maximum advantage from immunotherapy, it is crucial to investigate predictive biomarkers. This review provides a summary of the currently identified biomarkers associated with the extent of benefit from immuno-monotherapy or immunotherapy combined with chemotherapy in patients with advanced NSCLC. These biomarkers can be categorized into three groups: tumor-related, tumor-microenvironment-related, and host-factor-related.Tumor-related factors include PD-L1 expression, tumor mutational burden and specific genetic mutations, while tumor-microenvironment-related factors include extracellular vesicles and T-cell receptors, and host-related factors include systemic inflammation, circulating fatty acid profile, and the microbiome.

Patlak-Ki derived from ultra-high sensitivity dynamic total body [18F]FDG PET/CT correlates with the response to induction immuno-chemotherapy in locally advanced non-small cell lung cancer patients

PURPOSE

This study aimed to investigate the predictive value of metabolic features in response to induction immuno-chemotherapy in patients with locally advanced non-small cell cancer (LA-NSCLC), using ultra-high sensitivity dynamic total body [18F]FDG PET/CT.

METHODS

The study analyzed LA-NSCLC patients who received two cycles of induction immuno-chemotherapy and underwent a 60-min dynamic total body [18F]FDG PET/CT scan before treatment. The primary tumors (PTs) were manually delineated, and their metabolic features, including the Patlak-Ki, Patlak-Intercept, maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were evaluated. The overall response rate (ORR) to induction immuno-chemotherapy was evaluated according to RECIST 1.1 criteria. The Patlak-Ki of PTs was calculated from the 20-60 min frames using the Patlak graphical analysis. The best feature was selected using Laplacian feature importance scores, and an unsupervised K-Means method was applied to cluster patients. ROC curve was used to examine the effect of selected metabolic feature in predicting tumor response to treatment. The targeted next generation sequencing on 1021 genes was conducted. The expressions of CD68, CD86, CD163, CD206, CD33, CD34, Ki67 and VEGFA were assayed through immunohistochemistry. The independent samples t test and the Mann-Whitney U test were applied in the intergroup comparison. Statistical significance was considered at P < 0.05.

RESULTS

Thirty-seven LA-NSCLC patients were analyzed between September 2020 and November 2021. All patients received two cycles of induction chemotherapy combined with Nivolumab/ Camrelizumab. The Laplacian scores showed that the Patlak-Ki of PTs had the highest importance for patient clustering, and the unsupervised K-Means derived decision boundary of Patlak-Ki was 2.779 ml/min/100 g. Patients were categorized into two groups based on their Patlak-Ki values: high FDG Patlak-Ki (H-FDG-Ki, Patlak-Ki > 2.779 ml/min/100 g) group (n = 23) and low FDG Patlak-Ki (L-FDG-Ki, Patlak-Ki ≤ 2.779 ml/min/100 g) group (n = 14). The ORR to induction immuno-chemotherapy was 67.6% (25/37) in the whole cohort, with 87% (20/23) in H-FDG-Ki group and 35.7% (5/14) in L-FDG-Ki group (P = 0.001). The sensitivity and specificity of Patlak-Ki in predicting the treatment response were 80% and 75%, respectively [AUC = 0.775 (95%CI 0.605-0.945)]. The expression of CD3+/CD8+ T cells and CD86+/CD163+/CD206+ macrophages were higher in the H-FDG-Ki group, while Ki67, CD33+ myeloid cells, CD34+ micro-vessel density (MVD) and tumor mutation burden (TMB) were comparable between the two groups.

CONCLUSIONS

The total body [18F]FDG PET/CT scanner performed a dynamic acquisition of the entire body and clustered LA-NSCLC patients into H-FDG-Ki and L-FDG-Ki groups based on the Patlak-Ki. Patients with H-FDG-Ki demonstrated better response to induction immuno-chemotherapy and higher levels of immune cell infiltration in the PTs compared to those with L-FDG-Ki. Further studies with a larger patient cohort are required to validate these findings.

Tumor Mutational Burden in Breast Cancer: Current Evidence, Challenges, and Opportunities

Tumor mutational burden (TMB) correlates with tumor neoantigen burden, T cell infiltration, and response to immune checkpoint inhibitors in many solid tumor types. Based on data from the phase II KEYNOTE-158 study, the anti-PD-1 antibody pembrolizumab was granted approval for treating patients with advanced solid tumors and TMB ≥ 10 mutations per megabase. However, this trial did not include any patients with metastatic breast cancer; thus, several questions remain unanswered about the true role of TMB as a predictive biomarker of benefit to immune checkpoint inhibitor therapy in breast cancer. In this review, we will discuss the challenges and opportunities in establishing TMB as a predictive biomarker of benefit to immunotherapy in metastatic breast cancer.

Biomarker-directed, pembrolizumab-based combination therapy in non-small cell lung cancer: phase 2 KEYNOTE-495/KeyImPaCT trial interim results

Although pembrolizumab confers clinical benefit in non-small cell lung cancer (NSCLC), only a subset of patients will respond due to a heterogenous tumor microenvironment. KEYNOTE-495/KeyImPaCT is an ongoing biomarker-directed, adaptively randomized phase 2 study investigating first-line pembrolizumab (200 mg every 3 weeks) + lenvatinib (20 mg daily), anti-CTLA-4 quavonlimab (25 mg every 6 weeks) or anti-LAG-3 favezelimab (200 mg or 800 mg every 3 weeks) in advanced NSCLC. Patients were categorized by T-cell-inflamed gene expression profile (Tcell_infGEP) and tumor mutational burden (TMB) status and randomly assigned 1:1:1 to receive pembrolizumab + lenvatinib, pembrolizumab + quavonlimab or pembrolizumab + favezelimab. The primary outcome was investigator-assessed objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 using pre-specified efficacy thresholds for each biomarker-defined subgroup (>5% (Tcell_infGEP^lowTMB^non-high (group I)), >20% (Tcell_infGEP^lowTMB^high (group II) and Tcell_infGEP^non-lowTMB^non-high (group III)) and >45% (Tcell_infGEP^non-lowTMB^high (group IV))). Secondary outcomes were progression-free survival, overall survival and safety. At data cutoff, ORR ranges were 0-12.0% in group I, 27.3-33.3% in group II, 13.6-40.9% in group III and 50.0-60.0% in group IV. ORR with pembrolizumab + lenvatinib in group III met the pre-specified efficacy threshold. The safety profile of each treatment arm was consistent with the known safety profile of each combination. These data demonstrate the feasibility of prospective Tcell_infGEP and TMB assessment to study the clinical activity of first-line pembrolizumab-based combination therapies in advanced NSCLC. ClinicalTrials.gov registration: NCT03516981 .

Association between gene expression signatures and clinical outcomes of pembrolizumab versus paclitaxel in advanced gastric cancer: exploratory analysis from the randomized, controlled, phase III KEYNOTE-061 trial

BACKGROUND

In the randomized, controlled, phase III KEYNOTE-061 trial, second-line pembrolizumab did not significantly prolong overall survival (OS) versus paclitaxel in patients with PD-L1-positive (combined positive score ≥1) advanced gastric/gastroesophageal junction (G/GEJ) cancer but did elicit a longer duration of response and offered a favorable safety profile. This prespecified exploratory analysis was conducted to evaluate associations between tumor gene expression signatures and clinical outcomes in the phase III KEYNOTE-061 trial.

METHODS

Using RNA sequencing data obtained from formalin-fixed, paraffin-embedded baseline tumor tissue samples, we evaluated the 18-gene T-cell-inflamed gene expression profile (TcellinfGEP) and 10 non-TcellinfGEP signatures (angiogenesis, glycolysis, granulocytic myeloid-derived suppressor cell (gMDSC), hypoxia, monocytic MDSC (mMDSC), MYC, proliferation, RAS, stroma/epithelial-to-mesenchymal transition/transforming growth factor-β, WNT). The association between each signature on a continuous scale and outcomes was analyzed using logistic (objective response rate (ORR)) and Cox proportional hazards regression (progression-free survival (PFS) and OS). One-sided (pembrolizumab) and two-sided (paclitaxel) p values were calculated for TcellinfGEP (prespecified α=0.05) and the 10 non-TcellinfGEP signatures (multiplicity-adjusted; prespecified α=0.10).

RESULTS

RNA sequencing data were available for 137 patients in each treatment group. TcellinfGEP was positively associated with ORR (p=0.041) and PFS (p=0.026) for pembrolizumab but not paclitaxel (p>0.05). The TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR (p=0.077), PFS (p=0.057), and OS (p=0.033) for pembrolizumab, while the TcellinfGEP-adjusted glycolysis (p=0.018), MYC (p=0.057), and proliferation (p=0.002) signatures were negatively associated with OS for paclitaxel.

CONCLUSIONS

This exploratory analysis of tumor TcellinfGEP showed associations with ORR and PFS for pembrolizumab but not for paclitaxel. TcellinfGEP-adjusted mMDSC signature was negatively associated with ORR, PFS, and OS for pembrolizumab but not paclitaxel. These data suggest myeloid-driven suppression may play a role in resistance to PD-1 inhibition in G/GEJ cancer and support a strategy of considering immunotherapy combinations which target this myeloid axis.

TRIAL REGISTRATION NUMBER

NCT02370498.

Clinicopathologic and Genomic Factors Impacting Efficacy of First-Line Chemoimmunotherapy in Advanced NSCLC

INTRODUCTION

Although programmed cell death protein 1 and programmed death-ligand 1 (PD-L1) blockade in combination with platinum-doublet chemotherapy has become a mainstay of first-line treatment for advanced NSCLC, factors associated with efficacy of chemoimmunotherapy (CIT) are not well characterized.

METHODS

In this multicenter retrospective analysis, clinicopathologic and genomic data were collected from patients with advanced NSCLC (lacking sensitizing genomic alterations in EGFR and ALK) and evaluated with clinical outcomes to first-line CIT.

RESULTS

Among 1285 patients treated with CIT, a worsening performance status and increasing derived neutrophil-to-lymphocyte ratio in the blood were associated with a significantly reduced objective response rate (ORR), median progression-free survival (mPFS), and median overall survival (mOS). With increasing PD-L1 tumor proportion scores of less than 1%, 1% to 49%, 50% to 89%, and greater than or equal to 90%, there was a progressive improvement in ORR (32.7% versus 37.5% versus 51.6% versus 61.7%, p < 0.001), mPFS (5.0 versus 6.1 versus 6.8 versus 13.0 mo, p < 0.001), and generally mOS (12.9 versus 14.6 versus 34.7 versus 23.1 mo, p = 0.009), respectively. Of 789 NSCLCs with comprehensive genomic data, NSCLCs with a tumor mutational burden (TMB) greater than or equal to the 90th percentile had an improved ORR (53.5% versus 36.4%, p = 0.004), mPFS (10.8 versus 5.5 mo, p < 0.001), and mOS (29.2 versus 13.1 mo, p < 0.001), compared with those with a TMB less than the 90th percentile. In all-comers with nonsquamous NSCLC, the presence of an STK11, KEAP1, or SMARCA4 mutation was associated with significantly worse ORR, mPFS, and mOS to CIT (all p < 0.05); this was also observed in the KRAS-mutant subgroup of NSCLCs with co-occurring mutations in STK11, KEAP1, or SMARCA4 (all p < 0.05). In KRAS wild-type NSCLC, KEAP1 and SMARCA4 mutations were associated with a significantly shorter mPFS and mOS to CIT (all p < 0.05), but STK11 mutation status had no significant impact on mPFS (p = 0.16) or mOS (p = 0.38).

CONCLUSIONS

In advanced NSCLC, better patient performance status, low derived neutrophil-to-lymphocyte ratio, increasing PD-L1 expression, a very high TMB, and STK11/KEAP1/SMARCA4 wild-type status are associated with improved clinical outcomes to first-line CIT.

Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell lung cancer

The use of immune checkpoint inhibitors (ICIs) has become mainstream in the treatment of non-small cell lung cancer (NSCLC). The idea of harnessing the immune system to fight cancer is fast developing. Neoadjuvant treatment in NSCLC is undergoing unprecedented change. Chemo-immunotherapy combinations not only seem to achieve population-wide treating coverage irrespective of PD-L1 expression but also enable achieving a pathological complete response (pCR). Despite these recent advancements in neoadjuvant chemo-immunotherapy, not all patients respond favorably to treatment with ICIs plus chemo and may even suffer from severe immune-related adverse effects (irAEs). Similar to selection for target therapy, identifying patients most likely to benefit from chemo-immunotherapy may be valuable. Recently, several prognostic and predictive factors associated with the efficacy of neoadjuvant immunotherapy in NSCLC, such as tumor-intrinsic biomarkers, tumor microenvironment biomarkers, liquid biopsies, microbiota, metabolic profiles, and clinical characteristics, have been described. However, a specific and sensitive biomarker remains to be identified. Recently, the construction of prediction models for ICI therapy using novel tools, such as multi-omics factors, proteomic tests, host immune classifiers, and machine learning algorithms, has gained attention. In this review, we provide a comprehensive overview of the different positive prognostic and predictive factors in treating preoperative patients with ICIs, highlight the recent advances made in the efficacy prediction of neoadjuvant immunotherapy, and provide an outlook for joint predictors.

Using genomic scars to select immunotherapy beneficiaries in advanced non-small cell lung cancer

In advanced non-small cell lung cancer (NSCLC), response to immunotherapy is difficult to predict from pre-treatment information. Given the toxicity of immunotherapy and its financial burden on the healthcare system, we set out to identify patients for whom treatment is effective. To this end, we used mutational signatures from DNA mutations in pre-treatment tissue. Single base substitutions, doublet base substitutions, indels, and copy number alteration signatures were analysed in [Formula: see text] patients (the discovery set). We found that tobacco smoking signature (SBS4) and thiopurine chemotherapy exposure-associated signature (SBS87) were linked to durable benefit. Combining both signatures in a machine learning model separated patients with a progression-free survival hazard ratio of 0.40[Formula: see text] on the cross-validated discovery set and 0.24[Formula: see text] on an independent external validation set ([Formula: see text]). This paper demonstrates that the fingerprints of mutagenesis, codified through mutational signatures, select advanced NSCLC patients who may benefit from immunotherapy, thus potentially reducing unnecessary patient burden.

Clinical Benefit of First-Line Programmed Death-1 Antibody Plus Chemotherapy in Low Programmed Cell Death Ligand 1-Expressing Esophageal Squamous Cell Carcinoma: A Post Hoc Analysis of JUPITER-06 and Meta-Analysis

PURPOSE

Pembrolizumab or nivolumab plus chemotherapy was approved as a first-line treatment for high programmed cell death ligand 1 (PD-L1)-expressing esophageal squamous cell carcinoma (ESCC) by the European Medicines Agency, whereas the US Food and Drug Administration approved this regimen regardless of PD-L1 expression. The superiority of programmed death-1 (PD-1) antibody plus chemotherapy over chemotherapy alone in patients with low PD-L1-expressing ESCC remains debatable.

METHODS

Post hoc analysis of the Chinese JUPITER-06 study focusing on efficacy stratified by PD-L1 tumor proportion score (TPS; using JS311 antibody) was conducted. Electronic databases were searched to identify eligible randomized controlled trials for meta-analysis. Study-level pooled analyses of hazard ratios (HRs) for overall survival and progression-free survival and odds ratios for objective response rate according to PD-L1 expression were performed.

RESULTS

The post hoc analysis of JUPITER-06 showed more prominent clinical benefit with PD-1 antibody plus chemotherapy than with chemotherapy alone in both the high and low PD-L1-expressing subgroups. Five randomized controlled trials were included in the meta-analysis, and two PD-L1 expression scoring criteria, TPS (≥ 1%/< 1%) and combined positive score (CPS, ≥ 10/< 10), were analyzed. Significant overall survival benefit by adding PD-1 antibody to chemotherapy was observed in both the TPS < 1% (HR, 0.74; 95% CI, 0.56 to 0.97) and CPS < 10 (HR, 0.77; 95% CI, 0.66 to 0.89) subgroups. Similarly, significantly prolonged progression-free survival was observed in both the TPS < 1% (HR, 0.66; 95% CI, 0.50 to 0.86) and CPS < 10 (HR, 0.63; 95% CI, 0.47 to 0.84) subgroups. In addition, the objective response rate of the TPS < 1% subgroup was significantly improved (odds ratio, 1.71; 95% CI, 1.27 to 2.29). In all high PD-L1-expressing subgroups, the pooled benefit of PD-1 antibody plus chemotherapy was significantly better than that of chemotherapy.

CONCLUSION

This study provided novel evidence supporting the superiority of PD-1 antibody plus chemotherapy to chemotherapy alone in patients with advanced ESCC with low PD-L1 expression. Further studies of predictive biomarkers are warranted.

Immunotherapeutics in lung cancers: from mechanistic insight to clinical implications and synergistic perspectives

BACKGROUND

Lung cancer is one of the highly lethal forms of cancer whose incidence has worldwide rapidly increased over the past few decades. About 80-85% of all lung cancer cases constitute non-small cell lung cancer (NSCLC), with adenocarcinoma, squamous cell carcinoma and large cell carcinoma as the main subtypes. Immune checkpoint inhibitors have led to significant advances in the treatment of a variety of solid tumors, significantly improving cancer patient survival rates.

METHODS AND RESULTS

The cytotoxic drugs in combination with anti-PD-(L)1 antibodies is a new method that aims to reduce the activation of immunosuppressive and cancer cell prosurvival responses while also improving direct cancer cell death. The most commonly utilized immune checkpoint inhibitors for patients with non-small cell lung cancer are monoclonal antibodies (Atezolizumab, Cemiplimab, Ipilimumab, Pembrolizumab etc.) against PD-1, PD-L1, and CTLA-4. Among them, Atezolizumab (TECENTRIQ) and Cemiplimab (Libtayo) are engineered monoclonal anti programmed death ligand 1 (PD-L1) antibodies that inhibit binding of PD-L1 to PD-1 and B7.1. As a result, T-cell proliferation and cytokine synthesis are inhibited leading to restoring the immune homeostasis to fight cancer cells.

CONCLUSIONS

In this review article, the path leading to the introduction of immunotherapeutic options in lung cancer treatment is described, with analyzing the benefits and shortages of the current immunotherapeutic drugs. In addition, possibilities to co-administer immunotherapeutic agents with standard cancer treatment modalities are also considered.

Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction

Cuproptosis is a newly form of cell death. Cuproptosis related lncRNA in lung adenocarcinoma (LUAD) has also not been fully elucidated. In the present study, we aimed to construct a prognostic signature based on cuproptosis-related lncRNA in LUAD and investigate its association with immunotherapy response. The RNA-sequencing data, clinical information and simple nucleotide variation of LUAD patients were obtained from TCGA database. The LASSO Cox regression was used to construct a prognostic signature. The CIBERSORT, ESTIMATE and ssGSEA algorithms were applied to assess the association between risk score and TME. TIDE score was applied to reflect the efficiency of immunotherapy response. The influence of overexpression of lncRNA TMPO-AS1 on A549 cell was also assessed by in vitro experiments. The lncRNA prognostic signature included AL606834.1, AL138778.1, AP000302.1, AC007384.1, AL161431.1, TMPO-AS1 and KIAA1671-AS1. Low-risk group exhibited much higher immune score, stromal score and ESTIMATE score, but lower tumor purity compared with high-risk groups. Also, low-risk group was associated with a much higher score of immune cells and immune related function sets, indicating an immune activation state. Low-risk patients had relative higher TIDE score and lower TMB. External validation using IMvigor210 immunotherapy cohort demonstrated that low-risk group had a better prognosis and might more easily benefit from immunotherapy. Overexpression of lncRNA TMPO-AS1 promoted the proliferation, migration and invasion of A549 cell line. The novel cuproptosis-related lncRNA signature could predict the prognosis of LUAD patients, and helped clinicians stratify patients appropriate for immunotherapy and determine individual therapeutic strategies.

Durable responders in advanced NSCLC with elevated TMB and treated with 1L immune checkpoint inhibitor: a real-world outcomes analysis

BACKGROUND

For patients with advanced non-small cell lung carcinoma (NSCLC), immune checkpoint inhibitor (ICPI) and chemotherapy (chemo) ICPI represent two distinct first-line standard-of-care regimens without clear and established biomarkers to inform the optimal choice for individual patients. Here, we examined the complementary roles of tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) immunohistochemistry (IHC) to inform first-line therapy using a large real-world (rw) data set.

MATERIALS AND METHODS

The study included patients with NSCLC from an rw de-identified clinico-genomic database. All patients underwent genomic testing using Foundation Medicine's tissue comprehensive genomic profiling assay and PD-L1 IHC assay scored for tumor cell staining (TS).

RESULTS

Of 2165 patients included in the analysis, 150 exhibited durable benefit from first-line ICPI regimens (these patients were enriched for PD-L1 TS ≥50, non-squamous histology, and TMB ≥20 mutations/megabase (muts/Mb)). Comparing low TMB (<10 muts/Mb), high TMB (10-19 muts/Mb), and very high TMB (≥20 muts/Mb) receiving ICPI alone, we observed a stepwise increase in median rwPFS (real world-progression free survival) (6.5, 7.5, 17.2 months) and rwOS (real world-overall survival) (10.1, 11.8, 26.9 months) as TMB increased. In the low PD-L1 (TS <50%) cohort, TMB <20 muts/Mb showed a more favorable rwPFS (HR: 0.56 (95% CI: 0.40 to 0.79)) and rwOS (HR 0.74 (95% CI: 0.58 to 0.96)) on chemoICPI when compared with ICPI alone while the point estimate in rwPFS favored monoICPI in the TMB ≥20 muts/Mb cohort, the CI is wide and does not reach statistical significance (HR: 1.68 (95% CI: 0.52 to 5.48)).

CONCLUSION

This study provides evidence that higher TMB cut-offs, such as 20 muts/Mb, can identify patients with prolonged benefit from ICPI. TMB ≥20 muts/Mb is a potential biomarker that may identify patients in whom an ICPI without chemo could be considered, even in the setting of lower PD-L1 levels. Prospective validation of these findings could increase access to chemo-sparing regimens for the first-line treatment of advanced NSCLC.

Liquid Biopsy and Immuno-Oncology for Advanced Nonsmall Cell Lung Cancer

BACKGROUND

In the last decade, immune checkpoint inhibitors have revolutionized the treatment of metastatic nonsmall cell lung cancer without oncogenic addiction. Currently, programmed death ligand 1 (PD-L1) status, assessed in tissue biopsy samples, is the only test for guiding the prescription of these therapies in clinical practice. However, obtaining tumor tissue from patients with lung cancer is not always feasible and PD-L1 positivity is not a guarantee of immunotherapy efficacy. In this context, liquid biopsy, represented by several circulating biomarkers that reflect the tumor characteristics, is emerging as an interesting alternative approach.

CONTENT

We describe the main blood biomarkers evaluated in patients with metastatic nonsmall cell lung cancer before/during immune checkpoint inhibitor treatment, with a focus on circulating cell-free DNA, circulating tumor DNA (ctDNA), blood tumor mutational burden, and circulating tumor cells (CTCs).

SUMMARY

Monitoring of ctDNA and CTCs during immunotherapy may be a promising tool to help clinicians in therapeutic decision-making.

Predictive Biomarkers for Immunotherapy in Lung Cancer: Perspective From the International Association for the Study of Lung Cancer Pathology Committee

Immunotherapy including immune checkpoint inhibitors (ICIs) has become the backbone of treatment for most lung cancers with advanced or metastatic disease. In addition, they have increasingly been used for early stage tumors in neoadjuvant and adjuvant settings. Unfortunately, however, only a subset of patients experiences meaningful response to ICIs. Although programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry (IHC) has played a role as the principal predictive biomarker for immunotherapy, its performance may not be optimal, and it suffers multiple practical issues with different companion diagnostic assays approved. Similarly, tumor mutational burden (TMB) has multiple technical issues as a predictive biomarker for ICIs. Now, ongoing research on tumor- and host immune-specific factors has identified immunotherapy biomarkers that may provide better response and prognosis prediction, in particular in a multimodal approach. This review by the International Association for the Study of Lung Cancer Pathology Committee provides an overview of various immunotherapy biomarkers, including updated data on PD-L1 IHC and TMB, and assessments of neoantigens, genetic and epigenetic signatures, immune microenvironment by IHC and transcriptomics, and microbiome and pathologic response to neoadjuvant immunotherapies. The aim of this review is to underline the efficacy of new individual or combined predictive biomarkers beyond PD-L1 IHC and TMB.

Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer

The efficacy of immune checkpoint blockade (ICB) varies greatly among metastatic non-small cell lung cancer (NSCLC) patients. Loss of heterozygosity at the HLA-I locus (HLA-LOH) has been identified as an important immune escape mechanism. However, despite HLA-I disruptions in their tumor, many patients have durable ICB responses. Here we seek to identify HLA-I-independent features associated with ICB response in NSCLC. We use single-cell profiling to identify tumor-infiltrating, clonally expanded CD4⁺ T cells that express a canonical cytotoxic gene program and NSCLC cells with elevated HLA-II expression. We postulate cytotoxic CD4⁺ T cells mediate anti-tumor activity via HLA-II on tumor cells and augment HLA-I-dependent cytotoxic CD8⁺ T cell interactions to drive ICB response in NSCLC. We show that integrating tumor extrinsic cytotoxic gene expression with tumor mutational burden is associated with longer time to progression in a real-world cohort of 123 NSCLC patients treated with ICB regimens, including those with HLA-LOH.

Some cancer patients with impaired HLA-I still respond to immunotherapy. Here the authors combine a cytotoxic gene signature from CD4+ and CD8+ T cells with tumor mutational burden to predict immunotherapy response in NSCLC patients, including those with HLA-LOH.

Association of Tumor Mutational Burden with Efficacy of Pembrolizumab{plus minus}Chemotherapy as First-Line Therapy for Gastric Cancer in the Phase III KEYNOTE-062 Study

PURPOSE

This prespecified exploratory analysis evaluated the association between tumor mutational burden (TMB) status and outcomes of first-line pembrolizumab{plus minus}chemotherapy versus chemotherapy in KEYNOTE-062.

EXPERIMENTAL DESIGN

In patients with advanced gastric cancer and evaluable TMB data, we evaluated the association between TMB (continuous variable; square root scale) assessed with FoundationOne® CDx and clinical outcomes [ORR, PFS, and OS] using logistic (ORR) and Cox proportional hazards (PFS, OS) regression models. Clinical utility of TMB was assessed using the prespecified cutoff of 10mut/Mb.

RESULTS

TMB data were available for 306 of 763 patients (40.1%; pembrolizumab, 107; pembrolizumab+chemotherapy, 100; chemotherapy, 99). TMB was significantly associated with clinical outcomes in patients treated with pembrolizumab and pembrolizumab+chemotherapy (ORR, PFS, and OS; all P<0.05) but not with chemotherapy (all P>0.05). The overall prevalence of TMB {greater than or equal to}10mut/Mb was 16% across treatment groups; 44% of patients who had TMB {greater than or equal to}10mut/Mb had high microsatellite instability (MSI-H) tumors. Improved clinical outcomes (ORR, PFS, and OS) were observed in pembrolizumab-treated patients (pembrolizumab monotherapy and pembrolizumab+chemotherapy) with TMB {greater than or equal to}10mut/Mb. When the analysis was limited to the non-MSI-H subgroup, both the positive association between clinical outcomes with pembrolizumab or pembrolizumab+chemotherapy and TMB as a continuous variable and the clinical utility of pembrolizumab (with or without chemotherapy) versus chemotherapy by TMB cutoff were attenuated.

CONCLUSIONS

This exploratory analysis of KEYNOTE-062 suggests an association between TMB and clinical efficacy with first-line pembrolizumab-based therapy in patients with advanced gastric/gastroesophageal junction adenocarcinoma. However, after the exclusion of patients with MSI-H tumors, the clinical utility of TMB was attenuated.

A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy

Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.

Digital gene expression analysis of NSCLC-patients reveals strong immune pressure, resulting in an immune escape under immunotherapy

BACKGROUND

Immune checkpoint inhibitors (ICIs) are currently one of the most promising therapy options in the field of oncology. Although the first pivotal ICI trial results were published in 2011, few biomarkers exist to predict their therapy outcome. PD-L1 expression and tumor mutational burden (TMB) were proven to be sometimes-unreliable biomarkers. We have previously suggested the analysis of processing escapes, a qualitative measurement of epitope structure alterations under immune system pressure, to provide predictive information on ICI response. Here, we sought to further validate this approach and characterize interactions with different forms of immune pressure.

METHODS

We identified a cohort consisting of 48 patients with advanced non-small cell lung cancer (NSCLC) treated with nivolumab as ICI monotherapy. Tumor samples were subjected to targeted amplicon-based sequencing using a panel of 22 cancer-associated genes covering 98 mutational hotspots. Altered antigen processing was predicted by NetChop, and MHC binding verified by NetMHC. The NanoString nCounter® platform was utilized to provide gene expression data of 770 immune-related genes. Patient data from 408 patients with NSCLC were retrieved from The Cancer Genome Atlas (TCGA) as a validation cohort.

RESULTS

The two immune escape mechanisms of PD-L1 expression (TPS score) (n = 18) and presence of altered antigen processing (n = 10) are mutually non-exclusive and can occur in the same patient (n = 6). Both mechanisms have exclusive influence on different genes and pathways, according to differential gene expression analysis and gene set enrichment analysis, respectively. Interestingly, gene expression patterns associated with altered processing were enriched in T cell and NK cell immune activity. Though both mechanisms influence different genes, they are similarly linked to increased immune activity.

CONCLUSION

Pressure from the immune system will lay the foundations for escape mechanisms, leading to acquisition of resistance under therapy. Both PD-L1 expression and altered antigen processing are induced similarly by pronounced immunoactivity but in different context. The present data help to deepen our understanding of the underlying mechanisms behind those immune escapes.

Immunotherapy in Lung Cancer: Are the Promises of Long-Term Benefit Finally Met?

Over the last few years, agents targeting immune checkpoints have shown potential to improve therapeutic outcomes in patients with lung cancer in multiple clinical settings. Inhibitors of PD-1/PD-L1 have been approved for the treatment of different types of lung cancer by the FDA either alone or in combination with chemotherapy or other immune checkpoint inhibitors, such as anti-CTLA-4 agents. The introduction of these agents in clinical practice has revolutionized the therapeutic approach to lung cancer, keeping the promises of long-term benefit in selected patient populations. The therapeutic indications of immunotherapy in lung cancer are rapidly growing, and multiple combinations entered clinical practice or are under active development. Furthermore, the quest for a reliable predictive biomarker is still ongoing to overcome the limits of currently approved tests for patients' selection. In this review, we summarized the current status and progress of anti-PD-1/PD-L1 agents in lung cancer treatment.

Insertion-deletion rate is a qualitative aspect of the tumor mutation burden associated with the clinical outcomes of gastric cancer patients treated with nivolumab

BACKGROUND

We aimed to investigate the clinical implications of the tumor mutation burden (TMB) and insertion-deletion (indel) rate in gastric cancer patients treated with nivolumab.

METHODS

A total of 105 patients with advanced gastric cancer who were treated with nivolumab as third or later line of therapy were included as the study population. The indel rate was defined as the proportion of indels making up the TMB.

RESULTS

The median age was 58 (32-78 years), and 65 (61.9%) were men. Patients with TMB > 18.03/Mb showed superior progression-free survival (PFS) and overall survival (OS) compared to those with TMB ≤ 18.03/Mb. Patients with a high indel rate (> 40%) had a favorable PFS and OS compared to those with a lower indel rate (≤ 40%) (P = 0.009 and P = 0.007, respectively). The association between a high indel rate and favorable PFS and OS was prominent in a subgroup with TMB > 18.03/Mb (P < 0.001 and P = 0.007 for PFS and OS, respectively), but not in that with TMB ≤ 18.03/Mb. All five patients with deficient-MMR fell into the category of 'TMB > 18.03/Mb with an indel rate of > 40%. TMB ≥ 18.03/Mb with an indel rate of > 40% was independently associated with a favorable PFS (hazard ratio [HR] 0.07, P = 0.012) and OS (HR 0.09, P = 0.023).

CONCLUSION

TMB and indel rate should be jointly considered to better predict survival outcomes of gastric cancer patients treated with nivolumab. Our findings deserve further investigation and validation in future studies.

Plasma complement C7 as a target in non-small cell lung cancer patients to implement 3P medicine strategies

Background

Programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) immune checkpoint inhibitors (ICIs) significantly affect outcomes in non-small cell lung cancer (NSCLC) patients. However, differences in reactions toward PD-1/PD-L1 ICI among patients impose inefficient treatment. Therefore, developing a reliable biomarker to predict PD-1/PD-L1 ICI reaction is highly necessary for predictive, preventive, and personalized (3P) medicine.

Materials and methods

We recruited 63 patients from the National Cancer Center (NCC) and classified them into the training and validation sets. Next, 99 patients were recruited for inclusion into the external validation set at the Samsung Medical Center (SMC). Proteomic analysis enabled us to identify plasma C7 levels, which were significantly different among groups classified by their overall response to the RECIST V 1.1-based assessment. Analytical performance was evaluated to predict the PD-1/PD-L1 ICI response for each type of immunotherapy, and NSCLC histology was evaluated by determining the C7 levels via ELISA.

Results

Plasma C7 levels were significantly different between patients with and without clinical benefits (PFS ≥ 6 months). Among the groups sorted by histology and PD-1/PD-L1 immunotherapy type, only the predicted accuracy for pembrolizumab-treated patients from both NCC and SMC was greater than 73%. In patients treated with pembrolizumab, C7 levels were superior to those of the companion diagnostics 22C3 (70.3%) and SP263 (62.1%). Moreover, for pembrolizumab-treated patients for whom the PD-L1 tumor proportion score (TPS) was < 50%, the predictive accuracy of C7 was nearly 20% higher than that of 22C3 and SP263.

Conclusion

Evaluation of plasma C7 levels shows an accurate prediction of NSCLC patient reactions on pembrolizumab. It demonstrates plasma C7 is an alternative and supportive biomarker to overcome the predictive limitation of previous 22C3 and SP263. Thus, it is clear that clinical use of plasma C7 allows predictive diagnosis on lung cancer patients who have not been successfully treated with current CDx and targeted prevention on metastatic diseases in secondary care caused by a misdiagnosis of current CDx. Reduction of patients' financial burden and increased efficacy of cancer treatment would also enable prediction, prevention, and personalization of medical service on NSCLC patients. In other words, plasma C7 provides efficient medical service and an optimized medical economy followed which finally promotes the prosperity of 3P medicine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00266-x.

Tumor copy-number alterations predict response to immune-checkpoint-blockade in gastrointestinal cancer

Background

Despite the great achievements made in immune-checkpoint-blockade (ICB) in cancer therapy, there are no effective predictive biomarkers in gastrointestinal (GI) cancer.

Methods

This study included 93 metastatic GI patients treated with ICBs. The first cohort comprising 73 GI cancer patients were randomly assigned into discovery (n=44) and validation (n=29) cohorts. Comprehensive genomic profiling was performed on all samples to determine tumor mutational burden (TMB) and copy-number alterations (CNAs). A subset of samples was collected for RNA immune oncology (IO) panel sequencing, microsatellite instability (MSI)/mismatch repair and program death ligand 1 (PD-L1) expression evaluation. In addition, 20 gastric cancer (GC) patients were recruited as the second validation cohort.

Results

In the first cohort of 73 GI cancer patients, a lower burden of CNA was observed in patients with durable clinical benefit (DCB). In both the discovery (n=44) and validation (n=29) subsets, lower burden of CNA was associated with an improved clinical benefit and better overall survival (OS). Efficacy also correlated with a higher TMB. Of note, a combinatorial biomarker of TMB and CNA may better stratify DCB patients from ICB treatment, which was further confirmed in the second validation cohort of 20 GC patients. Finally, patients with lower burden of CNA revealed increased immune signatures in our cohort and The Cancer Genome Atlas data sets as well.

Conclusions

Our results suggest that the burden of CNA may have superior predictive value compared with other signatures, including PD-L1, MSI and TMB. The joint biomarker of CNA burden and TMB may better stratify DCB patients, thereby providing a rational choice for GI patients treated with ICBs.

Emerging Biomarkers for the Selection of Advanced NSCLC-Affected Immunotherapy Patients

Immunotherapy in the form of ICIs has revolutionized advanced NSCLC treatment algorithms, with ICI-containing combination treatments being the latest addition to approved regimens. However, PD-L1 still represents the only routinely assessed and validated biomarker apart from genetic drivers testing, impairing our capacity to personalize and guide treatment. Therefore, this paper aims to analyze the most promising emerging predictive biomarkers that could help us in the near future to select patients more effectively.

Low Infiltration of CD8+ PD-L1+ T Cells and M2 Macrophages Predicts Improved Clinical Outcomes After Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Carcinoma

Background

Many clinical studies have shown that patients with non-small cell lung carcinoma (NSCLC) can benefit from immune checkpoint inhibitor (ICI) therapy; however, PD-L1 and tumor mutation burden (TMB), which are recommended by the NCCN guidelines, are still insufficient in predicting the response to and prognosis of immunotherapy. Given the widespread use of ICIs, it is important to find biomarkers that can predict immunotherapy outcomes in NSCLC patients, and the exploration of additional effective biomarkers for ICI therapy is urgently needed.

Methods

A total of 33 stage II-IV NSCLC patients were included in this study. We analyzed immune markers in biopsy and surgical tissue resected from these patients before treatment with ICIs. We examined the infiltration of immune cells and expression of PD-L1 in immune cells using fluorescent multiplex immunohistochemistry (mIHC) stained with CD8/CD68/CD163/PD-L1 antibodies.

Results

In this cohort, we observed that the levels of CD8+ T cells, CD8+PD-L1+ T cells, and CD68+CD163+ M2 macrophages in the total region were independent prognostic factors for progression-free survival (PFS) in NSCLC patients treated with ICIs (HR=0.04, P=0.013; HR=17.70, P=0.026; and HR=17.88, P=0.011, respectively). High infiltration of CD8+ T cells and low infiltration of CD8+PD-L1+ T cells throughout the region were correlated with prolonged PFS (P=0.016 and P=0.02, respectively). No statistically significant difference was observed for CD68+CD163+ M2 macrophages. The joint parameters CD8+ high/CD8+PD-L1+ low, CD8+ high/CD68+CD163+ low and CD8+PD-L1+ low/CD68+CD163+ low predicted better PFS than other joint parameters (P<0.01, P<0.01, and P<0.001, respectively), and they also demonstrated stronger stratification than single biomarkers. The response rate of patients with high infiltration of CD8+ T cells was significantly higher than that of those with low infiltration (P<0.01), and the joint parameters CD8+/CD8+PD-L1+ and CD8+/CD68+CD163+ also demonstrated stronger stratification than single biomarkers.

Conclusions

This retrospective study identified the predictive value of CD8+PD-L1+ T cells, CD8+ T cells, and CD68+CD163+ M2 macrophages in NSCLC patients who received ICIs. Interestingly, our results indicate that the evaluation of joint parameters has certain significance in guiding ICI treatment in NSCLC patients.

The prognostic impact of tumor mutational burden (TMB) in the first-line management of advanced non-oncogene addicted non-small-cell lung cancer (NSCLC): a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

The role of tumor mutational burden (TMB) is still debated for selecting advanced non-oncogene addicted non-small-cell lung cancer (NSCLC) patients who might benefit from immune checkpoint inhibitors (ICIs). Of note, TMB failed to predict a benefit in overall survival (OS) among such patients.

MATERIALS AND METHODS

The purpose of this meta-analysis was to compare efficacy outcomes among first-line immune-oncology (IO) agents versus standard platinum-based chemotherapy (CT) within two subgroups (TMB-low and TMB-high on either tissue or blood). We collected hazard ratios (HRs) to evaluate the association for progression-free survival (PFS) and OS, with the relative 95% confidence intervals (CIs). Risk ratios (RRs) were used as an association measure for objective response rate (ORR).

RESULTS

Eight different cohorts of five randomized controlled phase III studies (3848 patients) were analyzed. In TMB-high patients, IO agents were associated with improved ORR (RRs 1.37, 95% CI 1.13-1.66), PFS (HR 0.69, 95% CI 0.61-0.79) and OS (HR 0.67, 95% CI 0.59-0.77) when compared with CT, thus suggesting a possible predictive role of high TMB for IO regimens. In TMB-low patients, the IO strategy did not lead to any significant benefit in survival and activity, whereas the pooled results of both ORR and PFS were intriguingly associated with a statistical significance in favor of CT.

CONCLUSIONS

This meta-analysis resulted in a proven benefit in OS in favor of IO agents in the TMB-high population. Although more prospective data are warranted, we postulated the hypothesis that monitoring TMB, in addition to the existing programmed death-ligand 1 (PD-L1) expression level, could represent the preferable option for future clinical research in the first-line management of advanced non-oncogene addicted NSCLC patients.

Molecular determinants of clinical outcomes with pembrolizumab versus paclitaxel in a randomized, open-label, phase III trial in patients with gastroesophageal adenocarcinoma

BACKGROUND

In the phase III KEYNOTE-061 trial (NCT02370498), pembrolizumab did not significantly improve overall survival versus paclitaxel as second-line therapy for gastric/gastroesophageal junction (GEJ) adenocarcinoma with programmed death-ligand 1 (PD-L1) combined positive score (CPS) ≥1 tumors. The association of tissue tumor mutational burden (tTMB) status and clinical outcomes was determined, including the relationship with CPS and microsatellite instability-high (MSI-H) status.

PATIENTS AND METHODS

In patients with whole exome sequencing (WES) data [420/592 (71%); pembrolizumab, 218; paclitaxel, 202], the association of tTMB with objective response rate (ORR; logistic regression), progression-free survival (PFS; Cox proportional hazards regression), and overall survival (OS; Cox proportional hazards regression) were measured using one-sided (pembrolizumab) and two-sided [paclitaxel] P values. tTMB was also evaluated using FoundationOne®CDx [205/592 (35%)]. Prespecified equivalent cut-offs of 175 mut/exome for WES and 10 mut/Mb for FoundationOne®CDx were used.

RESULTS

WES-tTMB was significantly associated with ORR, PFS, and OS in pembrolizumab-treated (all P < 0.001) but not paclitaxel-treated patients (all P > 0.6) in univariate analysis. The area under the receiver operating characteristics curve for WES-tTMB and response was 0.68 [95% confidence interval (CI) 0.56-0.81] for pembrolizumab and 0.51 (95% CI 0.39-0.63) for paclitaxel in univariate analysis. There was low correlation between WES-tTMB and CPS in both treatment groups (r ≤ 0.16). WES-tTMB remained significantly associated with all clinical endpoints with pembrolizumab after adjusting for CPS and with PFS and OS after excluding known MSI-H tumors (n = 26). FoundationOne®CDx-tTMB demonstrated a positive association with ORR, PFS, and OS in pembrolizumab-treated patients (all P ≤ 0.003) but not PFS or OS in paclitaxel-treated patients (P > 0.1).

CONCLUSION

This exploratory analysis from KEYNOTE-061 is the first to demonstrate a strong association between tTMB and efficacy with pembrolizumab but not paclitaxel in patients with gastric/GEJ adenocarcinoma in a randomized setting. Data further suggest tTMB is a significant and independent predictor beyond PD-L1 status.

Tumor mutational burden assessment in non-small-cell lung cancer samples: results from the TMB2 harmonization project comparing three NGS panels

Background

Tumor mutational burden (TMB) is a recently proposed predictive biomarker for immunotherapy in solid tumors, including non-small cell lung cancer (NSCLC). Available assays for TMB determination differ in horizontal coverage, gene content and algorithms, leading to discrepancies in results, impacting patient selection. A harmonization study of TMB assessment with available assays in a cohort of patients with NSCLC is urgently needed.

Methods

We evaluated the TMB assessment obtained with two marketed next generation sequencing panels: TruSight Oncology 500 (TSO500) and Oncomine Tumor Mutation Load (OTML) versus a reference assay (Foundation One, FO) in 96 NSCLC samples. Additionally, we studied the level of agreement among the three methods with respect to PD-L1 expression in tumors, checked the level of different immune infiltrates versus TMB, and performed an inter-laboratory reproducibility study. Finally, adjusted cut-off values were determined.

Results

Both panels showed strong agreement with FO, with concordance correlation coefficients (CCC) of 0.933 (95% CI 0.908 to 0.959) for TSO500 and 0.881 (95% CI 0.840 to 0.922) for OTML. The corresponding CCCs were 0.951 (TSO500-FO) and 0.919 (OTML-FO) in tumors with <1% of cells expressing PD-L1 (PD-L1<1%; N=55), and 0.861 (TSO500-FO) and 0.722 (OTML-FO) in tumors with PD-L1≥1% (N=41). Inter-laboratory reproducibility analyses showed higher reproducibility with TSO500. No significant differences were found in terms of immune infiltration versus TMB. Adjusted cut-off values corresponding to 10 muts/Mb with FO needed to be lowered to 7.847 muts/Mb (TSO500) and 8.380 muts/Mb (OTML) to ensure a sensitivity >88%. With these cut-offs, the positive predictive value was 78.57% (95% CI 67.82 to 89.32) and the negative predictive value was 87.50% (95% CI 77.25 to 97.75) for TSO500, while for OTML they were 73.33% (95% CI 62.14 to 84.52) and 86.11% (95% CI 74.81 to 97.41), respectively.

Conclusions

Both panels exhibited robust analytical performances for TMB assessment, with stronger concordances in patients with negative PD-L1 expression. TSO500 showed a higher inter-laboratory reproducibility. The cut-offs for each assay were lowered to optimal overlap with FO.

Validation of a Targeted Next-Generation Sequencing Panel for Tumor Mutation Burden Analysis: Results from the Onconetwork Immuno-Oncology Consortium

Tumor mutation burden (TMB) is evaluated as a biomarker of response to immunotherapy. We present the efforts of the Onconetwork Immuno-Oncology Consortium to validate a commercial targeted sequencing test for TMB calculation. A three-phase study was designed to validate the Oncomine Tumor Mutational Load (OTML) assay at nine European laboratories. Phase 1 evaluated reproducibility and accuracy on seven control samples. In phase 2, six formalin-fixed, paraffin-embedded samples tested with FoundationOne were reanalyzed with the OTML panel to evaluate concordance and reproducibility. Phase 3 involved analysis of 90 colorectal cancer samples with known microsatellite instability (MSI) status to evaluate TMB and MSI association. High reproducibility of TMB was demonstrated among the sites in the first and second phases. Strong correlation was also detected between mean and expected TMB in phase 1 (r² = 0.998) and phase 2 (r² = 0.96). Detection of actionable mutations was also confirmed. In colorectal cancer samples, the expected pattern of MSI-high/high-TMB and microsatellite stability/low-TMB was present, and gene signatures produced by the panel suggested the presence of a POLE mutation in two samples. The OTML panel demonstrated robustness and reproducibility for TMB evaluation. Results also suggest the possibility of using the panel for mutational signatures and variant detection. Collaborative efforts between academia and companies are crucial to accelerate the translation of new biomarkers into clinical research.

Prognostic and Predictive Biomarkers in Non-Small Cell Lung Cancer Patients on Immunotherapy-The Role of Liquid Biopsy in Unraveling the Puzzle

In the last decade, immunotherapy has been one of the most important advances in the non-small cell lung cancer (NSCLC) treatment landscape. Nevertheless, only a subset of NSCLC patients benefits from it. Currently, the only Food and Drug Administration (FDA) approved diagnostic test for first-line immunotherapy in metastatic NSCLC patients uses tissue biopsies to determine the programmed death ligand 1 (PD-L1) status. However, obtaining tumor tissue is not always feasible and puts the patient at risk. Liquid biopsy, which refers to the tumor-derived material present in body fluids, offers an alternative approach. This less invasive technique gives real-time information on the tumor characteristics. This review addresses different promising liquid biopsy based biomarkers in NSCLC patients that enable the selection of patients who benefit from immunotherapy and the monitoring of patients during this therapy. The challenges and the opportunities of blood-based biomarkers such as cell-free DNA (cfDNA), circulating tumor cells (CTCs), exosomes, epigenetic signatures, microRNAs (miRNAs) and the T cell repertoire will be addressed. This review also focuses on the less-studied feces-based and breath-based biomarkers.

PD-(L)1 Inhibitors as Monotherapy for the First-Line Treatment of Non-Small-Cell Lung Cancer Patients with High PD-L1 Expression: A Network Meta-Analysis

Programmed cell death-ligand 1 (PD-L1) has emerged as a potential biomarker for selection of patients more likely to respond to immunotherapy and as a prognostic factor in non-small cell lung cancer (NSCLC). In this network meta-analysis, we aimed to evaluate the efficacy of first-line anti-PD-(L)1 monotherapy in advanced NSCLC patients with high PD-L1 expression (≥50%) compared to platinum-based chemotherapy. We also evaluated efficacy outcomes according to tumor mutational burden (TMB). To that end, we conducted a systematic review. Six clinical trials with 2111 patients were included. In head-to-head comparisons, immunotherapy showed a significant improvement in progression-free survival (PFS: HRpooled = 0.69, 95% CI: 0.52-0.90, p = 0.007), overall survival (OS: HRpooled = 0.69, 95% CI: 0.61-0.78; p < 0.001) and overall response rate (ORR) (Risk ratio (RR)pooled = 1.354, 95% CI: 1.04-1.762, p = 0.024). In the assessment of relative efficacy for PFS through indirect comparisons, pembrolizumab (results from KEYNOTE-024) ranked highest followed by cemiplimab and atezolizumab, with statistical significance determined for some of the drugs. In terms of OS, cemiplimab ranked highest followed by atezolizumab and pembrolizumab, although non-significant OS was determined for these drugs. In conclusion, PD-(L)1 inhibitor monotherapy improves efficacy outcomes in the first line setting of advanced NSCLC patients with high PD-L1 expression. Evaluations with longer follow up are still needed to determine the superiority of any specific drug.

Recognizing Prognostic and Predictive Biomarkers in the Treatment of Non-Small Cell Lung Cancer (NSCLC) with Immune Checkpoint Inhibitors (ICIs)

Immunotherapy plays a central role in the treatment of NSCLC and biomarkers predicting response to ICIs are valuable therapeutic tools. Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is integral in therapy selection as its positive predictive nature to ICIs in the metastatic setting is well documented. Tumor mutational burden (TMB) has undergone much study and, while results are somewhat mixed, there is evidence for its positive predictive value with ICI use. Additional markers such as tumor-infiltrating lymphocytes (TILs), gene expression profiling (GEP), mismatch repair (MMR) and microsatellite instability (MSI), somatic mutations, neutrophil to leukocyte ratio (NLR), smoking history, medication history, and immune-related adverse event (irAE) development can further guide clinicians.

Biomarkers of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer: Beyond PD-L1

Immunotherapy has markedly improved the survival rate of patients with non-small cell lung cancer (NSCLC) and has introduced a new era in lung cancer treatment. Although some patients achieve durable responses to checkpoint blockade, not all experience such benefits, and some suffer from significant immunotoxicities. Thus, it is crucial to identify potential biomarkers suitable for screening the population that may benefit from immunotherapy. Based on the current clinical trials, the aim of the present study was to review the biomarkers for immune checkpoint inhibition that may have the potential to predict the response to immunotherapy in patients with lung cancer. A non-systematic literature review was done. We searched for eligible randomized controlled trials (RCTs) from PubMed, Embase, and the Cochrane Central Register of Controlled Trials from January 2015 to January 2021. The keywords included biomarkers, immunotherapy, immune checkpoint inhibition, programmed death ligand 1 (PD-L1), and non-small cell lung cancer. Additional biomarkers beyond PD-L1 that have been shown to have predictive capacity include tumor mutational burden, microsatellite instability, lung immune prognostic index, gut microbiome, and certain alterations in genes (eg, STK11 deletion, LKB1 kinase mutation, MDM2/4 amplification) that confer immunoresistance. The biomarkers reviewed in this article could help us better select the appropriate immunotherapy treatment for patients with NSCLC.

Efficacy and safety of sintilimab in combination with chemotherapy in previously untreated advanced or metastatic nonsquamous or squamous NSCLC: two cohorts of an open-label, phase 1b study

Combining chemotherapy with immunotherapy improves the therapeutic outcome for first-line (1L) patients with advance nonsmall-cell lung cancer (NSCLC). Two cohorts of a phase 1b study (NCT02937116) aimed to evaluate the safety and efficacy of sintilimab, a PD-1 inhibitor, plus chemotherapy in 1L patients with nonsquamous and squamous NSCLC (nsqNSCLC/sqNSCLC); and to identify potential biomarkers for treatment response. Treatment-naïve patients with nsqNSCLC were enrolled and intravenously given sintilimab (200 mg), pemetrexed (500 mg/m2), and cisplatin (75 mg/m2), every 3 weeks (Q3W) for 4 cycles in cohort D. Treatment-naïve patients with sqNSCLC were enrolled and intravenously given sintilimab (200 mg), gemcitabine (1250 mg/m2), and cisplatin (75 mg/m2), Q3W, for 6 cycles in cohort E. The primary objective was to evaluate the safety and efficacy of the treatment. The additional objective was to explore biomarkers for the treatment efficacy. Twenty-one patients with nsqNSCLC, and 20 patients with sqNSCLC were enrolled in cohort D and cohort E, respectively. By the data cutoff (April 17, 2019), 8 (38.1%) patients in cohort D and 17 (85.0%) patients in cohort E experienced grade 3-4 adverse events. The median follow-up duration was 16.4 months (14.8-23.0) in cohort D and 15.9 months (11.7-17.7) in cohort E. The objective response rate was 68.4% (95% CI 43.4%, 87.4%) in cohort D and 64.7% (95% CI 38.3%, 85.8%) in cohort E. Neither PD-L1 expression nor tumor mutation burden value was significantly associated with an improved treatment response. Sintilimab plus chemotherapy exhibited manageable toxicity and an encouraging antitumor activity in patients with nsqNSCLC and sqNSCLC.

The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker

Tumor mutational burden (TMB) reflects cancer mutation quantity. Mutations are processed to neo-antigens and presented by major histocompatibility complex (MHC) proteins to T cells. To evade immune eradication, cancers exploit checkpoints that dampen T cell reactivity. Immune checkpoint inhibitors (ICIs) have transformed cancer treatment by enabling T cell reactivation; however, response biomarkers are required, as most patients do not benefit. Higher TMB results in more neo-antigens, increasing chances for T cell recognition, and clinically correlates with better ICI outcomes. Nevertheless, TMB is an imperfect response biomarker. A composite predictor that also includes critical variables, such as MHC and T cell receptor repertoire, is needed.

DNA Sensing in Mismatch Repair-Deficient Tumor Cells Is Essential for Anti-tumor Immunity

Increased neoantigens in hypermutated cancers with DNA mismatch repair deficiency (dMMR) are proposed as the major contributor to the high objective response rate in anti-PD-1 therapy. However, the mechanism of drug resistance is not fully understood. Using tumor models defective in the MMR gene Mlh1 (dMLH1), we show that dMLH1 tumor cells accumulate cytosolic DNA and produce IFN-β in a cGAS-STING-dependent manner, which renders dMLH1 tumors slowly progressive and highly sensitive to checkpoint blockade. In neoantigen-fixed models, dMLH1 tumors potently induce T cell priming and lose resistance to checkpoint therapy independent of tumor mutational burden. Accordingly, loss of STING or cGAS in tumor cells decreases tumor infiltration of T cells and endows resistance to checkpoint blockade. Clinically, downregulation of cGAS/STING in human dMMR cancers correlates with poor prognosis. We conclude that DNA sensing within tumor cells is essential for dMMR-triggered anti-tumor immunity. This study provides new mechanisms and biomarkers for anti-dMMR-cancer immunotherapy.

Predictive Biomarkers for Immune Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer: Current Status and Future Directions

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment paradigm for advanced non-small cell lung cancer (NSCLC). Although certain patients achieve significant, long-lasting responses from checkpoint blockade, the majority of patients with NSCLC do not and may be unnecessarily exposed to inadequate therapies and immune-related toxicities. Therefore, there is a critical need to identify biomarkers predictive of immunotherapy response. While tumor and immune cell expression of programmed death ligand-1 and, more recently, tumor mutational burden are used in clinical practice and may correlate with immunotherapy response in selected circumstances, neither consistently predicts an individual patient's likelihood of clinical benefit from ICI therapy. More recently, innovative approaches such as blood-based assays and combination biomarker strategies are under active investigation. This review will focus on the current role and challenges of programmed death ligand-1 and tumor mutational burden as predictive biomarkers for immunotherapy response in advanced NSCLC and explore promising novel biomarker strategies.

Immune Modulation in Lung Cancer: Current Concepts and Future Strategies

Cancer immunotherapy represents the most dynamic field of biomedical research currently, with thoracic immuno-oncology as a forerunner. PD-(L)1 inhibitors are already part of standard first-line treatment for both non-small-cell and small-cell lung cancer, while unprecedented 5-year survival rates of 15-25% have been achieved in pretreated patients with metastatic disease. Evolving strategies are mainly aiming for improvement of T-cell function, increase of immune activation in the tumor microenvironment (TME), and supply of tumor-reactive lymphocytes. Several novel therapeutics have demonstrated preclinical efficacy and are increasingly used in rational combinations within clinical trials. Two overarching trends dominate: extension of immunotherapy to earlier disease stages, mainly as neoadjuvant treatment, and a shift of focus towards multivalent, individualized, mutatome-based antigen-specific modalities, mainly adoptive cell therapies and cancer vaccines. The former ensures ample availability of treated and untreated patient samples, the latter facilitates deeper mechanistic insights, and both in combination build an overwhelming force that is accelerating progress and driving the greatest revolution cancer medicine has seen so far. Today, immune modulation represents the most potent therapeutic modality in oncology, the most important topic in clinical and translational cancer research, and arguably our greatest, meanwhile justified hope for achieving cure of pulmonary neoplasms and other malignancies in the next future.

The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.

An increasing number of studies have demonstrated the benefit of tumor mutation burden (TMB), the number of non-silent mutations in the genome, as a predictive biomarker in a clinical setting. Most clinical trials utilize a smaller panel, instead of whole exome sequencing (WES), to estimate the exome-wide mutational load. However, the use of panels introduces panel size dependent sampling noise that could affect the performance of the TMB biomarker. In this work we create a mathematical model of the cancer histology, treatment response, and TMB device system to assess the interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy.

Emerging Blood-Based Biomarkers for Predicting Response to Checkpoint Immunotherapy in Non-Small-Cell Lung Cancer

Immune checkpoint inhibitors (ICIs) have brought impressive clinical benefits in a variety of malignancies over the past years, which dramatically revolutionized the cancer treatment paradigm. Monotherapy or in combination with chemotherapy of ICIs targeting programmed death 1/programmed death ligand 1 (PD-L1) has emerged as an alternative treatment for patients with advanced non-small-cell lung cancer (NSCLC). However, constrained by primary or acquired resistance, most patients obtain limited benefits from ICIs and occasionally suffer from severe immune-related adverse events. Moreover, owing to the complexity of the tumor microenvironment and the technical limitations, clinical application of PD-L1 and tumor mutation burden as biomarkers shows many deficiencies. Thus, additional predictive biomarkers are required to further advance the precision of proper patient selection, avoiding the exposure of potential non-responders to unnecessary immunotoxicity. Nowadays, an increasing number of investigations are focusing on peripheral blood as a noninvasive alternative to tissue biopsy in predicting and monitoring treatment outcomes. Herein, we summarize the emerging blood-based biomarkers that could predict the clinical response to checkpoint immunotherapy, specifically in patients with NSCLC.

Identification and Utilization of Biomarkers to Predict Response to Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICPI) have revolutionized cancer therapy and provided clinical benefit to thousands of patients. Despite durable responses in many tumor types, the majority of patients either fail to respond at all or develop resistance to the ICPI. Furthermore, ICPI treatment can be accompanied by serious adverse effects. There is an urgent need for identification of patient populations that will benefit from ICPI as single agents and when used in combinations. As ICPI have achieved regulatory approvals, accompanying biomarkers including PD-L1 immunohistochemistry (IHC) and tumor mutational burden (TMB) have also received approvals for some indications. The ICPI pembrolizumab was the first example of a tissue-agnostic FDA approval based on tumor microsatellite instability (MSI)/deficient mismatch repair (dMMR) biomarker status, rather than on tumor histology assessment. Several other ICPI-associated biomarkers are in the exploratory stage, including quantification of tumor-infiltrating lymphocytes (TILs), gene expression profiling (GEP) of an inflamed microenvironment, and neoantigen prediction. TMB and PD-L1 expression can predict a subset of responses, but they fail to predict all responses to checkpoint blockade. While a single biomarker is currently limited in its ability to fully capture the complexity of the tumor-immune microenvironment, a combination of biomarkers is emerging as a method to improve predictive power. Here we review the steadily growing impact of comprehensive genomic profiling (CGP) for development and utilization of predictive biomarkers by simultaneously capturing TMB, MSI, and the status of genomic targets that confer sensitivity or resistance to immunotherapy, as well as detecting inflammation through RNA expression signatures.