Anti-PD-1/PD-L1 Antibody Therapy for Pretreated Advanced or Metastatic Nonsmall Cell Lung Carcinomas and the Correlation between PD-L1 Expression and Treatment Effectiveness: An Update Meta-Analysis of Randomized Clinical Trials

Serum immune mediators as novel predictors of response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer patients with high tissue-PD-L1 expression

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related morbidity and mortality worldwide. Immune checkpoint inhibitors (ICIs) including anti-PD-1 and anti-PD-L1 antibodies, have significantly changed the treatment outcomes with better overall survival, but only 15-40% of the patients respond to ICIs therapy. The search for predictive biomarkers of responses is warranted for better clinical outcomes. We aim here to identify pre-treatment soluble immune molecules as surrogate biomarkers for tissue PD-L1 (TPD-L1) status and as predictors of response to anti-PD-1/PD-L1 therapy in NSCLC patients. Sera from 31 metastatic NSCLC patients, eligible for anti-PD-1/PD-L1 or combined chemoimmunotherapy, were collected prior to treatment. Analysis of soluble biomarkers with TPD-L1 status showed significant up/down regulation of the immune inhibitory checkpoint markers (sSiglec7, sSiglec9, sULBP4 and sPD-L2) in patients with higher TPD-L1 (TPD-L1 >50%) expression. Moreover, correlation analysis showed significant positive linear correlation of soluble PD-L1 (sPD-L1) with higher TPD-L1 expression. Interestingly, only responders in the TPD-L1 >50% group showed significant down regulation of the immune inhibitory markers (sPD-L2, sTIMD4, sNectin2 and CEA). When responders vs. non-responders were compared, significant down regulation of other immune inhibitory biomarkers (sCD80, sTIMD4 and CEA) was recorded only in responding patients. In this, the optimal cut-off values of CD80 <91.7 pg/ml and CEA <1614 pg/ml were found to be significantly associated with better progression free survival (PFS). Indeed, multivariate analysis identified the cutoff-value of CEA <1614 pg/ml as an independent predictor of response in our patients. We identified here novel immune inhibitory/stimulatory soluble mediators as potential surrogate/predictive biomarkers for TPD-L1 status, treatment response and PFS in NSCLC patients treated with anti-PD-1/PD-L1 therapy.

In vivo detection of circulating tumor cells predicts high-risk features in patients with bladder cancer

Previous studies have suggested the potential diagnostic value of circulating tumor cells (CTCs). This study aims to validate the efficacy of in vivo detection of CTCs in bladder cancer (BC) patients. A total of 216 BC patients were enrolled in this study. All patients had one in vivo detection of CTCs before initial treatment as a baseline parameter. The results of CTCs were associated with different clinicopathological features including molecular subtypes. PD-L1 expression on CTCs was also assessed and compared with its expression on tumors. CTC positive was defined as > 2 CTCs detected. Among all 216 patients, 49 (23%) were detected as CTC positive (> 2 CTCs) at baseline. Positive detection of CTCs was associated with multiple high-risk clinicopathological features including the multiplicity of the tumor (P = 0.02), tumor size (P < 0.01), tumor stage (P < 0.01), tumor grade (P < 0.01) and tumor PD-L1 expression (P = 0.01). The expression of PD-L1 on tumor and CTCs were not coordinated. Only 55% (74/134) matched the same status of PD-L1 expression on tumor and CTCs, along with 56 CTC ⁽⁺⁾ Tissue ^(-) and 4 CTC ^(-) Tissue ⁽⁺⁾ (P < 0.01). Our study has demonstrated the efficacy of in vivo detection of CTCs. The positive detection of CTCs is associated with multiple clinicopathological features. PD-L1 expression on CTCs has the potential to be a supplementary biomarker for immunotherapy.

Treatment Sequencing Strategies in Lung Cancer

BACKGROUND

The advances in the lung cancer screening methods and therapeutics, together with awareness towards deleterious habits, such as smoking, is increasing the overall survival with better quality of life for the patients. However, lung cancer is still one of the most common and fatal neoplasm with a high incidence and consequently burden to public health worldwide. Thus, based on guidelines and recent phases II and III clinical trials studies, this manuscript summarizes the current treatment sequencing strategies in lung cancer.

METHODS

A comprehensive search of related articles was performed focused on phases II and III clinical trials studies.

RESULTS

The lung cancer management should take into consideration the tumor characteristics, histology, molecular pathology and be discussed in a multidisciplinary team. Lung cancer treatment options comprises surgery whenever possible, radiotherapy associate with/or chemotherapy and immunotherapy as monotherapy, or combined with chemotherapy and best palliative care.

CONCLUSIONS

The screening predictability in more patients, smoking reduction, early diagnosis, better disease understanding and individualized, more effective and tolerable therapeutics are related to an increasing in overall survival and quality of life. In the near future improvement of personalized therapy in precision medicine is expected, enhancing new predictive biomarkers, optimal doses and optimal treatment sequencing as well as anti-cancer vaccines development.

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

Background

Clear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.

Methods

The gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan–Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs.

Results

Four immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9, and IL6. Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs.

Conclusion

A total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.

The Effectiveness and Safety of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer Patients With Stage III/IV: A Multicenter Study

Immune checkpoint inhibitors (ICIs) have been approved to treat patients with various cancer types, including lung cancer, in many countries. This study aims to investigate the effectiveness and safety of ICIs under different treatment conditions of non-small cell lung cancer patients. A population-based retrospective cohort study was conducted using the electronic health records of three medical centers in Taiwan. From January 01, 2016, to November 30, 2018, a total of 91 ICIs and 300 traditional chemotherapy users who had undergone stage III and IV lung cancer treatment were included in the study. We performed the randomized matched pair design by selecting a Chemotherapy subject for each ICI patient in the sample population. All subjects were monitored from the date of taking ICIs or chemotherapy drugs until the event of death, loss to follow-up, or were occurred with any defined adverse events. Kaplan-Meier estimators and cox proportional hazard regression models were used to compute the overall survival, efficacy, and safety of the ICIs group. The median overall survival (OS) in the ICI and Chemo groups after matching was 11.2 months and 10.5 months, respectively. However, the results showed no significant OS differences between ICIs and chemo groups for both before and after matching (HR,1.30; 95%CI, 0.68-2.46; p=0.428 before matching and HR,0.96; 95CI%, 0.64-1.44; p=0.838 after matching). We observed that with the higher amount of PD-L1, the length of the patients’ overall survival was (positive vs. negative PD-L1, HR,0.21; 95%CI, 0.05-0.80; p=0.022). The incidences of serious adverse drug events above grade 3 in the ICIs and traditional chemo groups were 12.7% and 21.5%, respectively. We also found that the number of AEs was less in ICIs than in the Chemo group, and the AEs that occurred after treatments were observed earlier in the ICIs compared to the Chemo group. ICIs drugs were observed to be safer than traditional chemotherapy as they had a lower risk of serious adverse drug events. It is necessary to pay attention to immune-related side effects and provide appropriate treatment. Furthermore, the patient’s physical status and PD-L1 test can be used to evaluate the clinical effectiveness of ICIs.

Rural barriers to early lung cancer detection: Exploring access to lung cancer screening programs in New Hampshire and Vermont

BACKGROUND

Rural populations face many health disadvantages compared to urban areas. There is a critical need to better understand the current lung cancer screening landscape in these communities to identify targeted areas to improve the impact of this proven tool.

METHODS

Data from the County Health Rankings of New Hampshire and Vermont was reviewed for population density, distribution of adult smokers, and level of education compared to the distribution of Lung Cancer Screening Facilities throughout these two states.

RESULTS

Screening programs in southern counties of Vermont with lower levels of education have decreased access. In New Hampshire, there are no programs within 30 miles of the areas with the largest distribution of smokers, and decreased access in some areas with the lowest levels of education.

CONCLUSIONS

Improving equitable access to high-quality screening services in rural regions and the creation of targeted interventions to address decreased access in areas of high tobacco use and low education is vital to decreasing the incidence of latestage presentations of lung cancer within these populations.

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.

Artificial Intelligence Tools for Refining Lung Cancer Screening

Nearly one-quarter of all cancer deaths worldwide are due to lung cancer, making this disease the leading cause of cancer death among both men and women. The most important determinant of survival in lung cancer is the disease stage at diagnosis, thus developing an effective screening method for early diagnosis has been a long-term goal in lung cancer care. In the last decade, and based on the results of large clinical trials, lung cancer screening programs using low-dose computer tomography (LDCT) in high-risk individuals have been implemented in some clinical settings, however, this method has various limitations, especially a high false-positive rate which eventually results in a number of unnecessary diagnostic and therapeutic interventions among the screened subjects. By using complex algorithms and software, artificial intelligence (AI) is capable to emulate human cognition in the analysis, interpretation, and comprehension of complicated data and currently, it is being successfully applied in various healthcare settings. Taking advantage of the ability of AI to quantify information from images, and its superior capability in recognizing complex patterns in images compared to humans, AI has the potential to aid clinicians in the interpretation of LDCT images obtained in the setting of lung cancer screening. In the last decade, several AI models aimed to improve lung cancer detection have been reported. Some algorithms performed equal or even outperformed experienced radiologists in distinguishing benign from malign lung nodules and some of those models improved diagnostic accuracy and decreased the false-positive rate. Here, we discuss recent publications in which AI algorithms are utilized to assess chest computer tomography (CT) scans imaging obtaining in the setting of lung cancer screening.

Expression and Clinical Significance of CMTM6 in Nonsmall Cell Lung Cancer

Chemokine-like factor (CKLF)-like MARVEL transmembrane domain containing protein 6 (CMTM6) is a ubiquitously expressed protein, which plays a critical role in the stability of programmed death-ligand 1. However, the expression of CMTM6 in a variety of cancer pathological tissues is not clear. Therefore, 109 patients who were diagnosed with nonsmall cell lung cancer (NSCLC) and underwent surgical resection were included in this retrospective study. The expression of CMTM6 in NSCLC patients' tissue samples were measured by immunohistochemistry and the results showed that 60 cases (55.05%) had high CMTM6 expression. The chi-square test showed that the expression of CMTM6 in NSCLC was significantly related to smoking (p = 0.017) and differentiation (p = 0.029). The Kaplan-Meier survival analysis suggested that the high expression of CMTM6 was associated with better prognosis of NSCLC patients. The univariate analysis revealed that the prognosis of NSCLC patients was correlated with T stage (p = 0.042), lymph node metastasis (p = 0.007), metastasis (p = 0.009), pathological differentiation (p = 0.001), and CMTM6 expression level (p < 0.001). In addition, multivariate analysis indicated that CMTM6 was an independent prognostic factor for NSCLC patients (p = 0.002). CMTM6 expression may have the potential to be a biomarker assisting in disease monitoring and prognosis in NSCLC.

PD-(L)1 Inhibitors in Combination with Chemotherapy as First-Line Treatment for Non-Small-Cell Lung Cancer: A Pairwise Meta-Analysis

The combination of programmed cell death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors with chemotherapy has emerged as a promising therapeutic option for advanced non-small-cell lung cancer (NSCLC). The aim of this meta-analysis was to evaluate the efficacy of the combined strategy in this setting. For this purpose, we performed a literature search of randomized controlled trials comparing PD-(L)1 inhibitors plus platinum-based chemotherapy versus chemotherapy alone in stage IV NSCLC patients. Seven clinical trials with 4562 patients were included. In the intention-to-treat wildtype population, PD-(L)1 inhibitor plus chemotherapy was significantly associated with improved progression-free survival (PFS) (Hazard ratio (HR) = 0.61, 95% confidence interval (CI): 0.57-0.65, p < 0.001) and overall survival (OS) (HR = 0.76, 95% CI: 0.67-0.86; p < 0.001) compared to chemotherapy. A significantly higher overall response rate (ORR) was also observed with the combined strategy (Odds ratio (OR) = 2.12, 95% CI: 1.70-2.63, p < 0.001). Furthermore, in all the analyzed subgroups, addition of PD-(L)1 inhibitors to chemotherapy significantly improved efficacy endpoints. Specifically, stratification according to PD-L1 expression revealed a benefit across all patients, regardless of their PFS status. In conclusion, PD-(L)1 blockade added to standard platinum-based chemotherapy significantly improved PFS, OS, and ORR in the up-front treatment of advanced NSCLC.

Predictive effect of PD-L1 expression for immune checkpoint inhibitor (PD-1/PD-L1 inhibitors) treatment for non-small cell lung cancer: A meta-analysis

BACKGROUND

Programmed death-ligand-1 (PD-L1) is a well-known predictive biomarker in non-small cell lung cancer (NSCLC) patients, however, its accuracy remains controversial. Here, we investigated the correlation between PD-L1 expression level and efficacy of its inhibitors, and hence assessed the predictive effect of PD-L1 expression.

METHODS

Studies that evaluated the efficacy of programmed death-1 (PD-1)/ PD-L1 inhibitors in advanced NSCLC patients according to tumor PD-L1 expression levels were searched for on Medline, Cochrane Library, and Embase. The pooled risk ratio (RR) and 95% confidence intervals (95% CIs) were calculated for the objective response rate (ORR) with overall survival (OS) and progression-free survival (PFS) were measured in terms of hazard ratio (HR) and the corresponding 95% CIs.

RESULTS

1432 NSCLC patients from six randomized controlled trials (RCTs) were included and three PD-1/PD-L1 inhibitors (atezolizumab, nivolumab, and pembrolizumab) were used to treat the patients. A significantly higher ORR was observed in the high PD-L1 expression group compared to the low expression group (0.35 [95% CI, 0.30-0.40] vs 0.11 [95% CI, 0.09-0.14]). The results of the subgroup analysis, grouped by the type of drugs and antibodies which assess immune checkpoint inhibitors were identical with the pooled result. However, our study showed that PD-L1 expression was neither prognostic nor predictive of overall survival (OS) or progression-free survival (PFS) in patients treated with PD-1/PD-L1 inhibitors compared to chemotherapy.

CONCLUSIONS

PD-L1 can be a predictive biomarker for ORR. Nevertheless, PD-L1 expression is not a good predictive tool for OS and PFS.

Association of PD-L1 expression status with the efficacy of PD-1/PD-L1 inhibitors and overall survival in solid tumours: A systematic review and meta-analysis

Whether PD-L1-positive patients derive more overall survival benefit from PD-1/PD-L1 inhibitors in the treatment of advanced solid tumours is unclear. We systematically searched the PubMed, Cochrane library and EMBASE databases from January 1, 1966 to March 1, 2019, to identify randomised controlled trials of PD-1/PD-L1 inhibitors (nivolumab, pembrolizumab, atezolizumab, durvalumab and avelumab) that had available hazard ratios (HRs) for death according to PD-L1 status. A random-effects model was used to calculate the pooled overall survival (OS) HR and 95% CI among PD-L1-positive and PD-L1-negative patients. An interaction test was performed to evaluate the heterogeneity between the two estimates. A total of 24 randomised trials, involving 12,966 participants, fulfilled the inclusion criteria. An OS benefit of PD-1/PD-L1 inhibitors was found in both PD-L1-positive patients (HR, 0.65; 95% CI, 0.60-0.70) and PD-L1-negative patients (HR, 0.82; 95% CI, 0.74-0.91) even at the minimum cut-off value of 1%. Significant differences in the efficacy of PD-1/PD-L1 inhibitors between PD-L1-positive and PD-L1-negative patients were noted at different cut-off values. Moreover, there was a positive dose-response relationship between PD-L1 positivity and OS benefit (HR for 1%, 0.58, [0.50, 0.67]; 5%, 0.52 [0.43, 0.64]; 10%, 0.50 [0.40, 0.63]). Subgroup analyses showed that these results were generally consistent, regardless of study design, line of treatment, treatment type, tumour type, PD-L1 staining cell type and median follow-up time. We demonstrated that PD-1/PD-L1 inhibitors significantly improved OS in both PD-L1 positive and PD-L1 negative patients compared to controls, but the magnitude of benefit was clinically PD-L1-dependent.

Immune cells within the tumor microenvironment: Biological functions and roles in cancer immunotherapy

The immune cells within the tumor microenvironment (TME) play important roles in tumorigenesis. It has been known that these tumor associated immune cells may possess tumor-antagonizing or tumor-promoting functions. Although the tumor-antagonizing immune cells within TME tend to target and kill the cancer cells in the early stage of tumorigenesis, the cancer cells seems to eventually escape from immune surveillance and even inhibit the cytotoxic function of tumor-antagonizing immune cells through a variety of mechanisms. The immune evasion capability, as a new hallmark of cancer, accidently provides opportunities for new strategies of cancer therapy, namely harnessing the immune cells to battle the cancer cells. Recently, the administrations of immune checkpoint modulators (represented by anti-CTLA4 and anti-PD antibodies) and adoptive immune cells (represented by CAR-T) have exhibited unexpected antitumor effect in multiple types of cancer, bringing a new era for cancer therapy. Here, we review the biological functions of immune cells within TME and their roles in cancer immunotherapy, and discuss the perspectives of the basic studies for improving the effectiveness of the clinical use.

The association of PD-L1 expression with the efficacy of anti-PD-1/PD-L1 immunotherapy and survival of non-small cell lung cancer patients: a meta-analysis of randomized controlled trials

Background

We conducted a meta-analysis to evaluate the efficacy of anti-programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) monotherapy or immunotherapy combined with chemotherapy and further estimated the value of PD-L1 expression in predicting the response from anti-PD-1/PD-L1 treatments as monotherapy or in combination with chemotherapy.

Methods

Clinical trial data were searched from electronic databases, which evaluated PD-1/PD-L1 inhibitors in non-small cell lung cancer (NSCLC) and correlated with PD-L1 expression levels.

Results

Fifteen randomized-controlled trials involving 10,074 patients were identified. Comparing anti-PD-1/PD-L1 monotherapy to chemotherapy, the pooled HR for overall survival (OS) was 0.77 (95% CI: 0.69-0.85, P<0.00001). Subgroup analyses revealed that patients had longer OS at ≥1%, ≥5%, ≥10% and ≥50% PD-L1 expression levels. Patients with higher PD-L1 expression may get increased benefit from PD-1/PD-L1 inhibitors. Moreover, patients with PD-L1 ≥50% had an objective response rate (ORR) improvement from anti-PD-1/PD-L1 therapy (RR =1.87, 95% CI: 1.27-2.75, P=0.001), but no ORR benefits were observed in patients with PD-L1 expression <1% (RR =0.82, 95% CI: 0.56-1.22, P=0.33) or 1-49% (RR =0.80, 95% CI: 0.64-0.98, P=0.03). OS was significantly better in patients receiving second-or-third line treatments (P<0.00001) with PD-L1 ≥1%. The efficacy of PD-1 inhibitors was similar to that of PD-L1 inhibitors, with no significant difference (P=0.63, I²=0%). Furthermore, immunotherapy combined with chemotherapy had better OS (HR =0.64, 95% CI: 0.48-0.84, P=0.001) than chemotherapy alone. Subgroup analyses showed that patients benefited from the combined chemo-IO treatment in the first-line setting regardless of PD-L1 expression level.

Conclusions

PD-L1 expression may be a valuable predictor of the efficacy of anti-PD-1/PD-L1 monotherapy in certain NSCLC patients. However, the combination of chemotherapy plus immunotherapy significantly improved survival regardless of the PD-L1 expression level in the first-line treatment of NSCLC.

Lung cancer survivors and employment: A systematic review

BACKGROUND

The aim of this systematic review is to identify, in a comprehensive manner, the impact of lung cancer on the employment status of survivors.

METHODS

The Preferred Reported Items for Systematic Reviews and Meta-analyses (PRISMA) statement was used as a formal guideline. The systematic review includes scientific papers published between January 2000 and October 2018. The search strategy queried the database MEDLINE. Inclusion criteria comprised: (1) inclusion of patients diagnosed with lung cancer (LC) (2); assessment of employment status or employment outcomes or work adjustments or return to work (3); inclusion of scientific papers published in peer-reviewed journals (4); inclusion of articles written either in English or in French. Literature reviews were not included.

RESULTS

A total of 642 scientific papers were retrieved. Twenty-three articles were included in the systematic review: 5 longitudinal studies and 18 cross-sectional studies. LC survivors are 2-3 times more likely to be unemployed as compared with control groups. Previous studies highlight a median duration of sickness absence increased for LC survivors compared to control groups. The strongest decline in earnings was observed among LC survivors as compared to other cancer types.

CONCLUSIONS

LC is associated with a significant impact on employment of patients. The promising results of recent therapeutic strategies could lead to a better social and professional prognosis. A reduction of indirect costs is to be expected.