Immunotherapy in nonsmall-cell lung cancer: current status and future prospects for liquid biopsy

Can blood-based markers predict RECIST progression in non-small cell lung cancer treated with immunotherapy?

PURPOSE

In this study, we aimed to evaluate the potential of routine blood markers, serum tumour markers and their combination in predicting RECIST-defined progression in patients with stage IV non-small cell lung cancer (NSCLC) undergoing treatment with immune checkpoint inhibitors.

METHODS

We employed time-varying statistical models and machine learning classifiers in a Monte Carlo cross-validation approach to investigate the association between RECIST-defined progression and blood markers, serum tumour markers and their combination, in a retrospective cohort of 164 patients with NSCLC.

RESULTS

The performance of the routine blood markers in the prediction of progression free survival was moderate. Serum tumour markers and their combination with routine blood markers generally improved performance compared to routine blood markers alone. Elevated levels of C-reactive protein (CRP) and alkaline phosphatase (ALP) ranked as the top predictive routine blood markers, and CYFRA 21.1 was consistently among the most predictive serum tumour markers. Using these classifiers to predict overall survival yielded moderate to high performance, even when cases of death-defined progression were excluded. Performance varied across the treatment journey.

CONCLUSION

Routine blood tests, especially when combined with serum tumour markers, show moderate predictive value  of RECIST-defined progression in NSCLC patients receiving immune checkpoint inhibitors. The relationship between overall survival and RECIST-defined progression may be influenced by confounding factors.

Multi-index comprehensive evaluation of the efficacy and response mechanism of immunotherapy in non-small cell lung cancer

OBJECTIVE

This research conducted multi-index comprehensive evaluations of the immunotherapeutic efficacy and response in non-small cell lung cancer (NSCLC).

METHODS

Forty-five patients with epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK) wild-type advanced NSCLC who received immunotherapy were included. Immunohistochemistry was adopted to detect the expression levels of programmed death ligand 1 (PD-L1) with X-ray cross-complementing protein 1 (XRCC1) and excision repair cross-complementing group 1 (ERCC1) proteins in tumor tissues. Flow cytometry was utilized to measure the levels of T-cell subsets in peripheral blood before and after treatment. PCR-RELP method was employed to evaluate XRCC1 and ERCC1 gene polymorphisms in peripheral blood. According to the treatment effect, patients evaluated as complete response (CR), partial response (PR), and stable disease (SD) were categorized into the immune response group, and patients evaluated as progressive disease (PD) were categorized into the immune unresponsive group. The correlation between PD-L1 protein expression, XRCC1 and ERCC1 protein expression, gene polymorphisms, T-cell subpopulation levels, and treatment efficacy was analyzed.

RESULTS

The therapeutic efficacy of patients with positive PD-L1 expression was better than that of patients with negative PD-L1 expression (P < 0.05). After treatment, peripheral blood CD3+ and CD4+ cell levels and Thl/Th2 cell levels were higher and CD8+ T cells were lower in the immune response group than in the immune unresponsive group (P < 0.05). Among the patients in the immune response group, peripheral blood CD3+ and CD4+ cell levels were higher and CD8+ T cells were lower in patients with positive PD-L1 expression than in patients with negative PD-L1 expression (P < 0.05). In the XRCC1 gene, the proportion of patients in the immune response group carrying the Arg/Trp + Trp/Trp genotype was higher than that of patients in the immune unresponsive group (P < 0.05). In the ERCC1 gene, the proportion of patients in the immune response group carrying the C/T + T/T genotype was higher than that of patients in the immune unresponsive group (P < 0.05). The positive expression rates of XRCC1 and ERCC1 in patients in the immune unresponsive group were higher than those in the immune response group (P < 0.05).

CONCLUSION

PD-L1 protein expression, XRCC1 and ERCC1 protein expression, and gene polymorphisms are associated with immunotherapy outcome in EGFR/ALK wild-type advanced NSCLC patients, and may be biological indicators for predicting immunotherapy outcome in EGFR/ALK wild-type advanced NSCLC patients.

Abnormal expression of Krüppel-like transcription factors and their potential values in lung cancer

Lung cancer still is one of the most common malignancy tumors in the world. However, the mechanisms of its occurrence and development have not been fully elucidated. Zinc finger protein family (ZNFs) is the largest transcription factor family in human genome. Recently, the more and more basic and clinical evidences have confirmed that ZNFs/Krüppel-like factors (KLFs) refer to a group of conserved zinc finger-containing transcription factors that are involved in lung cancer progression, with the functions of promotion, inhibition, dual roles and unknown classifications. Based on the recent literature, some of the oncogenic KLFs are promising molecular biomarkers for diagnosis, prognosis or therapeutic targets of lung cancer. Interestingly, a novel computational approach has been proposed by using machine learning on features calculated from primary sequences, the XGBoost-based model with accuracy of 96.4 % is efficient in identifying KLF proteins. This paper reviews the recent some progresses of the oncogenic KLFs with their potential values for diagnosis, prognosis and molecular target in lung cancer.

Pyroptosis-Derived Long Noncoding RNA Profiles Reveal a Novel Signature for Evaluating the Prognosis of Patients With Lung Adenocarcinoma

PURPOSE

Long noncoding RNAs (lncRNAs) were recently implicated in modifying pyroptosis. Nonetheless, pyroptosis-related lncRNAs and their possible clinical relevance persist largely uninvestigated in lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

A sum of 921 samples were collected from three independent data sets. We obtained pyroptosis-related genes from both the Molecular Signatures Database and relevant literature sources and used four machine learning techniques, comprising stepwise Cox, ridge regression, least absolute shrinkage and selection operator, and random forest. Multiple bioinformatics approaches were used to further investigate the underlying mechanisms.

RESULTS

In total, 39 differentially expressed pyroptosis genes were identified by comparing normal and tumor samples. Correlation analysis revealed 933 pyroptosis-related lncRNAs. Furthermore, univariate Cox regression determined 11 lncRNAs that exhibited stable associations with prognosis in the three cohorts, which were used to construct the pyroptosis-derived lncRNA signature. After analyzing the optimal results from four machine learning algorithms, we ultimately selected random forest to develop the pyroptosis-derived lncRNA signature. This signature was proven to be an independent prognostic factor and exhibited robust performance in three cohorts.

CONCLUSION

We provided novel insight and established a pyroptosis-derived lncRNA signature for patients with LUAD, exhibiting strong predictive capabilities in both the training and validation sets.

hccTAAb Atlas: An Integrated Knowledge Database for Tumor-Associated Autoantibodies in Hepatocellular Carcinoma

Tumor-associated autoantibodies (TAAbs) have demonstrated potential as biomarkers for cancer detection. However, the understanding of their role in hepatocellular carcinoma (HCC) remains limited. In this study, we aimed to systematically collect and standardize information about these TAAbs and establish a comprehensive database as a platform for in-depth research. A total of 170 TAAbs were identified from published papers retrieved from PubMed, Web of Science, and Embase. Following normative reannotation, these TAAbs were referred to as 162 official symbols. The hccTAAb (tumor-associated autoantibodies in hepatocellular carcinoma) atlas was developed using the R Shiny framework and incorporating literature-based and multiomics data sets. This comprehensive online resource provides key information such as sensitivity, specificity, and additional details such as official symbols, official full names, UniProt, NCBI, HPA, neXtProt, and aliases through hyperlinks. Additionally, hccTAAb offers six analytical modules for visualizing expression profiles, survival analysis, immune infiltration, similarity analysis, DNA methylation, and DNA mutation analysis. Overall, the hccTAAb Atlas provides valuable insights into the mechanisms underlying TAAb and has the potential to enhance the diagnosis and treatment of HCC using autoantibodies. The hccTAAb Atlas is freely accessible at https://nscc.v.zzu.edu.cn/hccTAAb/.

Trends and age, sex, and race disparities in time to second primary cancer from 1990 to 2019

BACKGROUND

Despite the growth in primary cancer (PC) survivors, the trends and disparities in this population have yet to be comprehensively examined using competing risk analysis. The objective is to examine trends in time to second primary cancer (SPC) and to characterize age, sex, and racial disparities in time-to-SPC.

METHODS

A retrospective analysis was conducted based on Surveillance, Epidemiology, and End Results (SEER). Two datasets for this study are (1) the discovery dataset with patients from SEER-8 (1990-2019) and (2) the validation dataset with patients from SEER-17 (2000-2019), excluding those in the discovery dataset. Patients were survivors of lung, colorectal, breast (female only), and prostate PCs.

RESULTS

The 5-year SPC cumulative incidences of lung PC increased from 1990 to 2019, with the cumulative incidence ratio being 1.73 (95% confidence intervals [CI], 1.64-1.82; p < 0.001). Age disparities among all PCs remained from 2010 to 2019, and the adjusted HRs (aHRs) of all PCs were above 1.43 when those below 65 were compared with those 65 and above. Sex disparity exists among colorectal and lung PC survivors. Racial disparities existed among non-Hispanic (NH) Black breast PC survivors (aHR: 1.11; 95% CI: 1.07-1.17; p < 0.001). The types of SPC vary according to PC and sex.

CONCLUSIONS

Over the past three decades, there has been a noticeably shortened time-to-SPC among lung PC survivors. This is likely attributed to the reduced number of lung cancer deaths due to advancements in effective treatments. However, disparities in age, sex, and race still exist, indicating that further effort is needed to close the gap.

Peripheral blood inflammatory biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

S100P as a potential biomarker for immunosuppressive microenvironment in pancreatic cancer: a bioinformatics analysis and in vitro study

BACKGROUND

Immunosuppression is a significant factor contributing to the poor prognosis of cancer. S100P, a member of the S100 protein family, has been implicated in various cancers. However, its role in the tumor microenvironment (TME) of pancreatic cancer remains unclear. This study aimed to investigate the potential impact of S100P on TME characteristics in patients with pancreatic cancer.

METHODS

Multiple data (including microarray, RNA-Seq, and scRNA-Seq) were obtained from public databases. The expression pattern of S100P was comprehensively evaluated in RNA-Seq data and validated in four different microarray datasets. Prognostic value was assessed through Kaplan-Meier plotter and Cox regression analyses. Immune infiltration levels were determined using the ESTIMATE and ssGSEA algorithms and validated at the single-cell level. Spearman correlation test was used to examine the correlation between S100P expression and immune checkpoint genes, and tumor mutation burden (TMB). DNA methylation analysis was performed to investigate the change in mRNA expression. Reverse transcription PCR (RT-PCR) and immunohistochemical (IHC) were utilized to validate the expression using five cell lines and 60 pancreatic cancer tissues.

RESULTS

This study found that S100P was differentially expressed in pancreatic cancer and was associated with poor prognosis (P < 0.05). Notably, S100P exhibited a significant negative-correlation with immune cell infiltration, particularly CD8 + T cells. Furthermore, a close association between S100P and immunotherapy was observed, as it strongly correlated with TMB and the expression levels of TIGIT, HAVCR2, CTLA4, and BTLA (P < 0.05). Intriguingly, higher S100P expression demonstrated a negative correlation with methylation levels (cg14323984, cg27027375, cg14900031, cg14140379, cg25083732, cg07210669, cg26233331, and cg22266967), which were associated with CD8 + T cells. In vitro RT-PCR validated upregulated S100P expression across all five pancreatic cancer cell lines, and IHC confirmed high S100P levels in pancreatic cancer tissues (P < 0.05).

CONCLUSION

These findings suggest that S100P could serve as a promising biomarker for immunosuppressive microenvironment, which may provide a novel therapeutic way for pancreatic cancer.

Landscape of tumor and immune system cells-derived exosomes in lung cancer: mediators of antitumor immunity regulation

The immune system plays a critical role in cancer, including lung cancer, which is the leading cause of cancer-related deaths worldwide. Immunotherapy, particularly immune checkpoint blockade, has revolutionized the treatment of lung cancer, but a large subset of patients either do not respond or develop resistance. Exosomes, essential mediators of cell-to-cell communication, exert a profound influence on the tumor microenvironment and the interplay between cancer and the immune system. This review focuses on the role of tumor-derived exosomes and immune cells-derived exosomes in the crosstalk between these cell types, influencing the initiation and progression of lung cancer. Depending on their cell of origin and microenvironment, exosomes can contain immunosuppressive or immunostimulatory molecules that can either promote or inhibit tumor growth, thus playing a dual role in the disease. Furthermore, the use of exosomes in lung cancer immunotherapy is discussed. Their potential applications as cell-free vaccines and drug delivery systems make them an attractive option for lung cancer treatment. Additionally, exosomal proteins and RNAs emerge as promising biomarkers that could be employed for the prediction, diagnosis, prognosis and monitoring of the disease. In summary, this review assesses the relationship between exosomes, lung cancer, and the immune system, shedding light on their potential clinical applications and future perspectives.

CYP19A1 promotes gastric cancer as part of a lipid metabolism-related gene signature related to the response of immunotherapy and prognosis

BACKGROUND

Increasing evidence suggests that the metabolism of lipids plays a crucial role in the progression of gastric cancer. However, the expression of lipid metabolism-related genes (LMGs) still does not serve as a prognostic biomarker in gastric cancer.

METHODS

We obtained transcriptome data for 751 LMGs and divided STAD patients into two subtypes based on differences in LMGs expression. Then, we analyzed genetic changes in two subtypes as well as immune features to determine their differences. We also constructed a prognostic risk model related to LMGs for individualized comprehensive evaluations.

RESULTS

In this study, two lipid metabolic (LM) subtypes were identified anchored in the expression profiles of LMGs. Clinical information, genomic alterations, immune features, and immunotherapy response varied significantly between the two LM subtypes. A risk model based on LMGs was also developed to assess prognosis and distinguish patients with high risk from those at low risk. The prognosis differed significantly between the two risk groups of patients. In STAD patients, the risk score was strongly correlated with genomic alterations and immune profile scores. Also, the risk score was an excellent predictor of immune checkpoint inhibitors (ICIs) response. Anchored in preliminary results derived from the aforementioned bioinformatic analysis, we chose CYP19A1 as our target gene and the expression of CYP19A1 was verified in several common gastric cancer cell lines. Then, we carried out the Western blotting, CCK-8 assay, colony formation assay, wound healing assay, and transwell assay to explore the effects of CYP19A1 on malignant biological behavior, and positive consequences were obtained.

CONCLUSIONS

In this study, STAD patients were divided into two subtypes based on LMGs expression. It is possible to assess the prognosis of a patient and the response to immunotherapy using the established prognostic risk model. A series of basic laboratory experiments also verified the functional role of CYP19A1 in gastric cancer.

The combination of circulating IgM and geriatric nutritional risk index predicts the prognostic of hepatocellular carcinoma patients who underwent immune checkpoint inhibitors

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have shown promise in hepatocellular carcinoma (HCC) treatment. With the increasing use of ICIs in cancer treatment, identifying biomarkers that can predict the prognosis of patients receiving ICIs is of great importance. We aimed to investigate the potential of circulating immunoglobulins and the combination of Geriatric Nutritional Risk Index (GNRI) with IgM to predict prognosis in patients with HCC who received ICIs.

METHODS

Clinical and pathological data were collected from 101 patients with HCC who were administered ICIs and underwent circulating immunoglobulin testing between January 2018 and December 2021. Survival analysis, Cox regression analysis, and nomogram construction were performed to evaluate the prognostic value of the indicators.

RESULTS

In the preliminary survival analysis, we observed a significant correlation between patient prognosis and IgM levels. Patients with low IgM had shorter survival times. Upon combining the GNRI with IgM, patients with low GNRI and IgM levels had shorter progression-free survival (PFS) and overall survival (OS) (P < 0.001). Additionally, GNRI-IgM had the highest area under the curve (AUC) and was identified as an independent prognostic marker in this study. The C-indices of the nomograms for PFS and OS were 0.797 (0.734-0.860) and 0.827 (0.778-0.876), respectively.

CONCLUSIONS

IgM was significantly associated with the prognosis of patients with HCC receiving ICIs. The combination of the GNRI with IgM provided superior prognostic value and served as an independent prognostic marker. The GNRI-IgM can be used to effectively identify patients with HCC who are responsive to ICIs.

Potential biomarkers for immunotherapy in non-small-cell lung cancer

For individuals with advanced or metastatic non-small cell lung cancer (NSCLC), the primary treatment is platinum-based doublet chemotherapy. Immune checkpoint inhibitors (ICIs), primarily PD-1/PD-L1 and CTLA-4, have been found to be effective in patients with NSCLC who have no EGFR/ALK mutations. Furthermore, ICIs are considered a standard therapy. The quantity of fresh immunogenic antigens discovered by cytotoxic T cells was measured by PD-L1 expression and tumor mutational burden (TMB), which were the first biomarkers assessed in clinical trials. However, immunotherapy did not have response efficacy markers similar to targeted therapy, highlighting the significance of newly developed biomarkers. This investigation aims to review the research on immunotherapy for NSCLC, focusing primarily on the impact of biomarkers on efficacy prediction to determine whether biomarkers may be utilized to evaluate the effectiveness of immunotherapy.

Single-cell RNA sequencing reveals the effects of anti-PD-L1 therapy on 3LL lung cancer model and its tumor microenvironment

PD-L1 is expressed on antigen-presenting cells and tumor cells, thus allows tumor cells to escape immune surveillance. Moreover, targeting PD-L1 was also recommended and selected as important immune checkpoint inhibitors (ICIs) strategy in the treatment of advanced cancers due to the safety and activity. However, the detailed alteration of tumor microenvironment (TME) upon anti-PD-L1 therapy in lung cancer tumor model still needs to be resolved. In our present study, first, we characterized PD-L1 expression in human lung adenocarcinoma tissues by using public data, then we established the subcutaneous tumor-bearing model by using murine lung cancer cell line 3LL to perform the anti-PD-L1 therapy and the single-cell RNA sequencing (scRNA-seq) to reveal the remodeling of TME. We confirmed that PD-L1 blockade significantly inhibited tumor progression in 3LL mouse lung cancer model. The scRNA-seq depicted the detailed TME landscape of 3LL tumor model upon anti-PD-L1 treatment. Five major populations according to the marker genes were identified, including tumor cells, stromal cells, myeloid cells, T cells, and NK cells. In addition, we found that anti-PD-L1 treatment enhanced tumor immunogenicity and promoted inflammation in TME and promoted cancer-associated fibroblasts (CAFs)-mediated T-cell migration and infiltration. We also found that anti-PD-L1 treatment can increase dendritic cells (DCs) population and enhance the antigen-presenting ability to CD8+T cells and promote the transition of monocytes to macrophages and tumor-associated macrophages 2 (TAM2) to TAM1. We also revealed that Nfatc1 was up-regulated in the anti-PD-L1 treatment group, the frequencies of effector CD8+T cells, exhausted CD8+T cells, cycling T cells, and NKT were increased, and the frequencies of conventional CD4+T cells, Treg, IFN-induced T cells, and γδT cells were decreased. Therefore, our scRNA-seq data of the lung cancer tumor model upon anti-PD-L1 treatment made a comprehensive presentation and description about the remodeling of TME and will benefit us to understand the underlying mechanisms and to design combinational therapeutic strategies based on anti-PD-L1 therapy against lung cancer.

Circulating immune cell dynamics as outcome predictors for immunotherapy in non-small cell lung cancer

The use of immune checkpoint inhibitors (ICIs) continues to transform the therapeutic landscape of non-small cell lung cancer (NSCLC), with these drugs now being evaluated at every stage of the disease. In contrast to these advances, little progress has been made with respect to reliable predictive biomarkers that can inform clinicians on therapeutic efficacy. All current biomarkers for outcome prediction, including PD-L1, tumor mutational burden or complex immune gene expression signatures, require access to tumor tissue. Besides the invasive nature of the sampling procedure, other disadvantages of tumor tissue biopsies are the inability to capture the complete spatial heterogeneity of the tumor and the difficulty to perform longitudinal follow-up on treatment. A concept emerges in which systemic immune events developing at a distance from the tumor reflect local response or resistance to immunotherapy. The importance of this cancer 'macroenvironment', which can be deciphered by comprehensive analysis of peripheral blood immune cell subsets, has been demonstrated in several cutting-edge preclinical reports, and is corroborated by intriguing data emerging from ICI-treated patients. In this review, we will provide the biological rationale underlying the potential of blood immune cell-based biomarkers in guiding treatment decision in immunotherapy-eligible NSCLC patients. Finally, we will describe new techniques that will facilitate the discovery of more immune cell subpopulations with potential to become predictive biomarkers, and reflect on ways and the remaining challenges to bring this type of analysis to the routine clinical care in the near future.

Plasma D-dimer and interleukin-6 are associated with treatment response and progression-free survival in advanced NSCLC patients on anti-PD-1 therapy

BACKGROUND/AIMS

Response to therapy after using immune checkpoint inhibitors (ICIs) is unpredictable due to significant interindividual variation in efficacy among advanced non-small cell lung cancer (NSCLC) patients. The current study centered on the identification of perivascular blood biomarkers for predicting the effectiveness of anti-programmed cell death protein 1 (anti-PD-1) treatment and progression-free survival (PFS) in advanced NSCLC patients, that could be applied to help determine how to change treatment plans therapeutic regimens for optimizing clinical benefits.

METHODS

A comprehensive review of 100 advanced or recurrent NSCLC patients receiving anti-PD-1 therapy (Camrelizumab, pembrolizumab, sintilimab, or nivolumab) was conducted between January 2018 and April 2021 in Tianjin Medical University Cancer Hospital. The cutoff values of D-dimer were selected from rom our previous study, and interleukin-6 (IL-6) was divided according to the median. Using computed tomography, tumor response was evaluated in accordance with the Response Assessment Criteria in Solid Tumors, version 1.1.

RESULTS

High IL-6 level in advanced NSCLC patients was predictive of low efficacy and a short PFS duration after anti-PD-1 therapy. An increased D-dimer value of 981 ng/mL was significantly predictive of disease progression in NSCLC patients treated with anti-PD-1 and high D-dimer expression predictive of short duration of PFS. Further studies on the correlation between IL-6, D-dimer, and anti-PD-1 efficacy in NSCLC patients stratified by gender revealed that D-dimer and IL-6 levels were significantly associated with the risk of PFS in male patients.

CONCLUSIONS

High IL-6 content in peripheral blood in patients with advanced non-small cell lung cancer may contribute to poor anti-PD-1 efficacy and short duration of PFS through inducing alterations in the tumor microenvironment. D-dimer in peripheral blood is predictive of hyperfibrinolysis and contributes to the release of tumor-driven specific factors, leading to poor effects of anti-PD-1 therapy.

Radiation and immune checkpoint inhibitors in the treatment of oligometastatic non-small-cell lung cancer: a practical review of rationale, recent data, and research questions

The combined use of stereotactic ablative radiotherapy (SABR) and immune checkpoint inhibitors (ICIs) is an emerging treatment paradigm for oligometastatic non-small-cell lung cancer (NSCLC). Recent phase I and II trial data suggest that SABR to multiple metastases in addition to ICI use is safe and effective with promising progression-free survival and overall survival signals. There is great interest in capitalizing on combined immunomodulation from these two modalities for the treatment of oligometastatic NSCLC. Ongoing trials seek to validate the safety, efficacy, and preferred sequencing of SABR and ICI. This narrative review of the role of SABR when combined with ICI in oligometastatic NSCLC discusses the rationale for this bimodality treatment, summarizes recent clinical trial evidence, and proposes key principles of management based on the available evidence.

Immunotherapy through the Lens of Non-Small Cell Lung Cancer

Immunotherapy has revolutionised anti-cancer treatment in solid organ malignancies. Specifically, the discovery of CTLA-4 followed by PD-1 in the early 2000s led to the practice-changing clinical development of immune checkpoint inhibitors (ICI). Patients with lung cancer, including both small cell (SCLC) and non-small cell lung cancer (NSCLC), benefit from the most commonly used form of immunotherapy in immune checkpoint inhibitors (ICI), resulting in increased survival and quality of life. In NSCLC, the benefit of ICIs has now extended from advanced NSCLC to earlier stages of disease, resulting in durable benefits and the even the emergence of the word 'cure' in long term responders. However, not all patients respond to immunotherapy, and few patients achieve long-term survival. Patients may also develop immune-related toxicity, a small percentage of which is associated with significant mortality and morbidity. This review article highlights the various types of immunotherapeutic strategies, their modes of action, and the practice-changing clinical trials that have led to the widespread use of immunotherapy, with a focus on ICIs in NSCLC and the current challenges associated with advancing the field of immunotherapy.

Personalized circulating tumor DNA detection to monitor immunotherapy efficacy and predict outcome in locally advanced or metastatic non-small cell lung cancer

OBJECTIVE

Immune checkpoint inhibitors (ICIs) or combined with chemotherapy exhibit substantial efficacy for the treatment of advanced non-small cell lung cancer (NSCLC). However, reliable biomarkers that can monitor response to first-line ICIs ± chemotherapy remain unclear.

METHODS

A total of 16 tumor tissues and 46 matched peripheral blood samples at baseline and during treatment were retrospectively collected from 19 locally advanced or metastatic NSCLC patients. The circulating tumor DNA (ctDNA) burden by tumor-informed assay was detected to monitor and predict the therapeutic response and survival of NSCLC patients treated with first-line ICIs or plus chemotherapy.

RESULTS

We found that ctDNA was only positively detected in one patient by tumor-agnostic assay with a mean variant allele fraction (VAF) of 6.40%, whereas it was positively detected in three patients by tumor-informed assay with a mean VAF of 8.83%, 0.154%, and 0.176%, respectively. Tumor-informed assays could sensitively detect ctDNA in 93.75% (15/16) of patients. Trends in the level of ctDNA from baseline to first evaluation was consistent with the radiographic changes. There was a greater decrease in ctDNA after treatment compared with baseline in patients with partial response compared to patients with stable disease/progressive disease. Patients with over a 50% reduction in ctDNA had a significant progression-free survival and overall survival benefit.

CONCLUSION

The tumor-informed assay was favorable for ctDNA detection, and early dynamic changes in plasma ctDNA may be a valuable biomarker for monitoring the efficacy and predicting the outcome in advanced NSCLC patients treated with first-line ICIs ± chemotherapy.

Metastases to the kidney from primary lung cancer : clinicopathological analysis of six cases in a single center

OBJECTIVES

Cancer metastasis to the kidney is a rare event. We retrospectively analyzed clinicopathologic characteristics in 6 cases of diagnosed renal metastases from primary lung cancer. We also provide clinical follow-up data and brief review of the literature.

METHODS

Immunohistochemistry was used to evaluate the expression of TTF-1, NapsinA, CK7, CK(AE1/AE3), P63, P40, CgA, PAX-8, GATA3 and Ki-67 in primary tumor and metastases. Additionally, the clinical characteristics, imaging features, diagnosis, and treatment were analyzed.

RESULTS

With the help of immunohistochemistry and combined clinical history, we found four cases were lung adenocarcinomas, one case was lung squamous cell carcinoma, and the other case was lung small cell carcinoma metastases to the kidney.The patients were all male by gender and had a mean age of 62 years, and metastasis to the left kidney were more universal. Most of the tumors histological grade originating from the lung were poorly-moderately differentiated, and the time to metastasis to the kidney was relatively short for squamous lung cancer and small cell lung cancer, while the time to metastasis for lung adenocarcinoma was related to its degree of differentiation. Overall, we found the prognosis of lung cancer patients with renal metastases were poor especially with multi-site metastases.

CONCLUSIONS

Distinguishing primary and secondary tumors of the kidney is essential to guide treatment and prevent unnecessary surgery, so clinical information, radiology, histological correlation of the primary tumor, and immunohistochemical findings help the pathologist determine correct diagnosis.

Immune-Checkpoint-Inhibitor Therapy-Principles and Relevance of Biomarkers for Pathologists and Oncologists

Immune-checkpoint-inhibitor (ICI) therapy has been one of the major advances in the treatment of a variety of advanced or metastatic tumors in recent years. Therefore, ICI-therapy is already approved in first-line therapy for multiple tumors, either as monotherapy or as combination therapy. However, there are relevant differences in approval among different tumor entities, especially with respect to PD-L1 testing. Different response to ICI-therapy has been observed in the pivotal trials, so PD-L1 diagnostic testing is used for patient selection. In addition to PD-L1 testing of tumor tissue, liquid biopsy provides a noninvasive way to monitor disease in cancer patients and identify those who would benefit most from ICI-therapy. This overview focuses on the use of ICI-therapy and how it relates to common and potential future biomarkers for patient-directed treatment planning.

Effects of Aidi injection on life quality and incidence of adverse reactions in patients with non-small cell lung cancer compared with traditional chemotherapy: a systematic review and meta-analysis

Objective

Although the clinical application value of Aidi injection when treating non-small cell lung cancer (NSCLC) patients is explained only by the effectiveness of a certain literature or the improvement of a certain evaluation index, and the result is not convincing. To evaluate the effect of Aidi injection on life quality and incidence of adverse reactions in patients with NSCLCcompared with traditional chemotherapy.

Methods

PubMed, EMBASE, ScienceDirect, Cochrane Library, China Journal full-text Database (CNKI), VIP full-text Database, Wanfang Database and Chinese Biomedical Literature data (CBM), search relevant Chinese and foreign periodicals, conference papers, degree papers, etc. were searched Database and China Biomedical Literature Database (CBM) to search case-control trials of Aidi injection when treating NSCLC patients. The retrieval period begins with the establishment of the database and ends when the database is closed. Cochrane Handbook 5.3 was adopted to assess the bias risk of each contained literature based on independently extracted data by two researchers. A meta-analysis of the collected data was carried out using RevMan5.3 statistical software.

Results

2306 articles were retrieved by computer database, 1422 articles were harvested by excluding repeated studies, 865 articles were harvested by preliminary reading of article titles and abstracts, and 533 articles were initially contained by excluding unrelated studies, reviews, case reports and uncontrolled articles, and then the full text of the literature was carefully read. Eight clinical controlled studies were finally included, with a total of 784 samples, after excluding 525 literatures with incomplete data and no primary outcome indicators. Data from the contained studies were not noticeably heterogeneous in the meta-analysis of treatment effectiveness. The fixed effect model analysis indicated that the treatment effective rate of the study group was noticeably better, and the difference was statistically significant(P<0.05). The findings of the heterogeneity test were clearly heterogeneous among the contained research data, according to the meta-analysis of the levels of T lymphocyte subsets following treatment. The random effect model analysis indicated that the improvement of the cellular immune function of the research group was obvious, and the difference was statistically significant (P<0.05). According to the meta-analysis of the life quality scores after treatment, data from the contained research were evidently heterogeneous, according to results of the heterogeneity test. The random effect model analysis indicated that the life quality of the study group was noticeably higher, and the difference was statistically significant (P<0.05). The levels of serum vascular endothelial growth factor (VEGF) after treatment were measured by meta. Data from the contained research were evidently heterogeneous, according to results of the heterogeneity test. Random effect model analysis indicated that the level of serum VEGF in the study group was noticeably lower, and the difference was not statistically significant (P>0.05). A meta-analysis was conducted on the incidence of adverse reactions after treatment. The results of the heterogeneity test indicated that data from the contained research were evidently heterogeneous. The incidence was noticeably lower, and the difference was statistically significant (P<0.05). The funnel chart was drawn based on the effective rate of treatment, the level of T lymphocyte subsets, the score of life quality, the level of serum VEGF and the incidence of adverse reactions, and the publication bias analysis was carried out. The results indicated that most of the funnel maps were symmetrical and a small part of them were asymmetrical, suggesting that despite the heterogeneity of the study and the small number of included literatures, a publication bias was apparent in the included literature.

Conclusion

Based on routine chemotherapy associated with Aidi injection, the therapeutic effect of NSCLC patients can be noticeably enhanced, the effective rate of treatment can be noticeably promoted, the immune function and life quality can be improved, and the incidence of adverse reactions is low, which is worth popularizing in clinical practice, but several studies and follow-ups are needed to improve methodological quality and to verify the results over a longer period of time.

Homogeneous, Simple, and Direct Analysis of Exosomal PD-L1 via Aptamer-Bivalent-Cholesterol-Anchor Assembly of DNAzyme (ABCzyme) for Tumor Immunotherapy

Breakthroughs in immune checkpoint inhibitor (ICI) therapy have revolutionized clinical tumor therapy. Immunohistochemistry (IHC) analysis of PD-L1 in tumor tissue has been used to predict the response to tumor immunotherapy, but the results are not reproducible, and IHC is invasive and cannot be used to monitor the dynamic changes in PD-L1 expression during treatment. Monitoring the expression level of the PD-L1 protein on exosomes (exosomal PD-L1) is promising for both tumor diagnosis and tumor immunotherapy. Here, we established an aptamer-bivalent-cholesterol-anchor assembly of DNAzyme (ABCzyme) analytical strategy that can directly detect exosomal PD-L1 with a minimum lower limit of detection of 5.21 pg/mL. In this way, we found that the levels of exosomal PD-L1 are significantly elevated in the peripheral blood of patients with progressive disease. The precise analysis of exosomal PD-L1 by the proposed ABCzyme strategy provides a potentially convenient method for the dynamic monitoring of tumor progression in patients who receive immunotherapy and proves to be a potential and effective liquid biopsy method for tumor immunotherapy.

Liquid biopsy on the horizon in immunotherapy of non-small cell lung cancer: current status, challenges, and perspectives

Non-small cell lung cancer (NSCLC) is one of the most threatening malignancies to human health and life. In most cases, patients with NSCLC are already at an advanced stage when they are diagnosed. In recent years, lung cancer has made great progress in precision therapy, but the efficacy of immunotherapy is unstable, and its response rate varies from patient to patient. Several biomarkers have been proposed to predict the outcomes of immunotherapy, such as programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). Nevertheless, the detection assays are invasive and demanding on tumor tissue. To effectively predict the outcomes of immunotherapy, novel biomarkers are needed to improve the performance of conventional biomarkers. Liquid biopsy is to capture and detect circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes in body fluids, such as blood, saliva, urine, pleural fluid and cerebrospinal fluid as samples from patients, so as to make analysis and diagnosis of cancer and other diseases. The application of liquid biopsy provides a new possible solution, as it has several advantages such as non-invasive, real-time dynamic monitoring, and overcoming tumor heterogeneity. Liquid biopsy has shown predictive value in immunotherapy, significantly improving the precision treatment of lung cancer patients. Herein, we review the application of liquid biopsy in predicting the outcomes of immunotherapy in NSCLC patients, and discuss the challenges and future directions in this field.

The current understanding of the immune landscape relative to radiotherapy across tumor types

Radiotherapy is part of the standard of care treatment for a great majority of cancer patients. As a result of radiation, both tumor cells and the environment around them are affected directly by radiation, which mainly primes but also might limit the immune response. Multiple immune factors play a role in cancer progression and response to radiotherapy, including the immune tumor microenvironment and systemic immunity referred to as the immune landscape. A heterogeneous tumor microenvironment and the varying patient characteristics complicate the dynamic relationship between radiotherapy and this immune landscape. In this review, we will present the current overview of the immunological landscape in relation to radiotherapy in order to provide insight and encourage research to further improve cancer treatment. An investigation into the impact of radiation therapy on the immune landscape showed in several cancers a common pattern of immunological responses after radiation. Radiation leads to an upsurge in infiltrating T lymphocytes and the expression of programmed death ligand 1 (PD-L1) which can hint at a benefit for the patient when combined with immunotherapy. In spite of this, lymphopenia in the tumor microenvironment of 'cold' tumors or caused by radiation is considered to be an important obstacle to the patient's survival. In several cancers, a rise in the immunosuppressive populations is seen after radiation, mainly pro-tumoral M2 macrophages and myeloid-derived suppressor cells (MDSCs). As a final point, we will highlight how the radiation parameters themselves can influence the immune system and, therefore, be exploited to the advantage of the patient.

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.

Liquid Biopsies in Lung Cancer

As lung cancer has the highest cancer-specific mortality rates worldwide, there is an urgent need for new therapeutic and diagnostic approaches to detect early-stage tumors and to monitor their response to the therapy. In addition to the well-established tissue biopsy analysis, liquid-biopsy-based assays may evolve as an important diagnostic tool. The analysis of circulating tumor DNA (ctDNA) is the most established method, followed by other methods such as the analysis of circulating tumor cells (CTCs), microRNAs (miRNAs), and extracellular vesicles (EVs). Both PCR- and NGS-based assays are used for the mutational assessment of lung cancer, including the most frequent driver mutations. However, ctDNA analysis might also play a role in monitoring the efficacy of immunotherapy and its recent accomplishments in the landscape of state-of-the-art lung cancer therapy. Despite the promising aspects of liquid-biopsy-based assays, there are some limitations regarding their sensitivity (risk of false-negative results) and specificity (interpretation of false-positive results). Hence, further studies are needed to evaluate the usefulness of liquid biopsies for lung cancer. Liquid-biopsy-based assays might be integrated into the diagnostic guidelines for lung cancer as a tool to complement conventional tissue sampling.

Extracellular Vesicles Released from Cancer Cells Promote Tumorigenesis by Inducing Epithelial to Mesenchymal Transition via β-Catenin Signaling

Lung cancer is the leading cause of cancer-related deaths globally, in part due to a lack of early diagnostic tools and effective pharmacological interventions. Extracellular vesicles (EVs) are lipid-based membrane-bound particles released from all living cells in both physiological and pathological states. To understand the effects of lung-cancer-derived EVs on healthy cells, we isolated and characterized EVs derived from A549 lung adenocarcinoma cells and transferred them to healthy human bronchial epithelial cells (16HBe14o). We found that A549-derived EVs carry oncogenic proteins involved in the pathway of epithelial to mesenchymal transition (EMT) that are regulated by β-catenin. The exposure of 16HBe14o cells to A549-derived EVs resulted in a significant increase in cell proliferation, migration, and invasion via upregulating EMT markers such as E-Cadherin, Snail, and Vimentin and cell adhesion molecules such as CEACAM-5, ICAM-1, and VCAM-1, with concomitant downregulation of EpCAM. Our study suggests a role for cancer-cell-derived EVs to induce tumorigenesis in adjacent healthy cells by promoting EMT via β-catenin signaling.

Clinical Utility and Application of Liquid Biopsy Genotyping in Lung Cancer: A Comprehensive Review

Precision medicine has revolutionized the therapeutic management of cancer patients with a major impact on non-small cell lung cancer (NSCLC), particularly lung adenocarcinoma, where advances have been remarkable. Tissue biopsy, required for tumor molecular testing, has significant limitations due to the difficulty of the biopsy site or the inadequacy of the histological specimen. In this context, liquid biopsy, consisting of the analysis of tumor-released materials circulating in body fluids, such as blood, is increasingly emerging as a valuable and non-invasive biomarker for detecting circulating tumor DNA (ctDNA) carrying molecular tumor signatures. In advanced/metastatic NSCLC, liquid biopsy drives target therapy by monitoring response to treatment and identifying eventual genomic mechanisms of resistance. In addition, recent data have shown a significant ability to detect minimal residual disease in early-stage lung cancer, underlying the potential application of liquid biopsy in the adjuvant setting, in early detection of recurrence, and also in the screening field. In this article, we present a review of the currently available data about the utility and application of liquid biopsy in lung cancer, with a particular focus on the approach to different techniques of analysis for liquid biopsy and a comparison with tissue samples as well as the potential practical uses in early and advanced/metastatic NSCLC.

Folate receptor-positive circulating tumor cell count, lymphocyte count and derived neutrophil-to- lymphocyte ratio for diagnosing lung cancer relapse

The folate receptor-positive circulating tumor cell (FR⁺-CTC) count can be used to improve the diagnosis rate of lung cancer. The lymphocyte count (LC) and derived neutrophil-to-lymphocyte ratio (dNLR) are involved in inflammatory processes. Whether the FR⁺-CTC count combined with the dNLR or LC is helpful for diagnosing lung cancer recurrence is not clear. Sixty-eight patients who were initially diagnosed with lung cancer and received first-line treatment were included. The clinicopathological characteristics, routine blood examination results and CTC examination results of the patients were collected. The role of the complete blood count and FR⁺-CTC count in lung cancer treatment response and prognosis was analyzed. The FR⁺-CTC count after treatment was significantly correlated with the T stage (p=0.005). Multivariate analysis showed that the pathological type and FR⁺-CTC count were independent predictors of disease-or progression-free survival (DFS/PFS) in patients with lung cancer (p=0.010 and p=0.030, respectively). The FR⁺-CTC count, LC and dNLR predicted the recurrence of lung cancer (sensitivity and specificity of the FR⁺-CTC count, 69.2% and 71.4%; the LC, 50.0% and 88.5%; and the dNLR, 50.0% and 88.1%, respectively). The FR⁺-CTC count combined with the LC or dNLR improved the diagnostic rate of lung cancer recurrence (sensitivity and specificity of the FR⁺-CTC count plus the LC, 53.8% and 90.5%, and the FR⁺-CTC count plus the dNLR, 73.1% and 73.8%, respectively). When these three indicators were combined to predict lung cancer recurrence, the AUC value was 0.817. The FR⁺-CTC count combined with the dNLR and/or LC after treatment can improve the diagnostic rate of lung cancer recurrence. A higher FR⁺-CTC count predicts worse DFS/PFS in patients with lung cancer.

Diagnosis, Monitoring, and Prognosis of Liquid Biopsy in Cancer Immunotherapy

Liquid biopsy (LB), as a minimally invasive method of gleaning insight into the dynamics of diseases through a patient fluid sample, represents an interesting tool that can advise in disease monitoring, treatment selection, early diagnosis, evaluation of the response, and prognosis. Cancer immunotherapy is a breakthrough in cancer treatment, which is now recognized as the "fourth pillar" of cancer treatment, after surgery, chemotherapy, and radiotherapy. Liquid biopsy offers a different befalling for beneath invasive diagnosis, real-time accommodating monitoring, and analysis options, involving the isolation of circulating biomarkers, such as cell-free DNA (cfDNA), circulating tumor cells (CTCs), exosomes, and microRNAs (miRNAs). The biomarkers herein have great potential to allow the realization of liquid biopsy for predicting the immunotherapy response and precision medicine. Liquid biopsy offers an alternative, less invasive approach to select cancer patients who would benefit from immunotherapy and to monitor patients during their disease course. This review focuses on the use of liquid biopsy in the immunotherapy treatment of patients with cancer. In this review, we addressed the different promising liquid biopsy-based biomarkers in cancer patients that enable the selection of patients who benefit from immunotherapy and the monitoring of patients during this therapy.

Prognostic value of genes related to cancer-associated fibroblasts in lung adenocarcinoma

BACKGROUND

Although it has been established that cancer-associated fibroblasts (CAFs) facilitate tumor development, the relationship between CAFs and the prognosis of patients with lung adenocarcinoma (LUAD) has not been extensively explored.

OBJECTIVE

This study was formulated to investigate the prognostic value of CAF-related genes in LUAD.

METHODS

Differential analysis was carried out with TCGA-LUAD dataset as the training set. By overlapping differentially expressed genes (DEGs) with genes associated with CAF, CAF-related DEGs specific to LUAD were obtained. A prognostic risk model was constructed by Lasso and Cox regression analysis, and samples were grouped according to median risk score. The efficacy of the model was accessed through survival curve and receiver operating characteristic curve (ROC) analyses, with the validation set for verification. Risk score combined with clinical factors was utilized for Cox analysis to verify the independence of the model, and a nomogram was drawn. GSEA was performed on different risk groups. Immunologic infiltration and tumor mutational burden were assessed in different risk groups.

RESULTS

Eleven feature genes including DLGAP5, KCNE2, UPK2, NPAS2, ARHGAP11A, ANGPTL4, ANLN, DKK1, SMUG1, C16orf74, and ACAD8 were identified, based on which a prognostic model was constructed. Risk score could predict the prognosis of LUAD patients and could be an independent prognostic factor for LUAD patients. GSEA outcomes displayed significant enrichment of genes in the high-risk group in the P53 SIGNALING PATHWAY. In comparison to the low-risk group, the high-risk group exhibited a decreased degree of immune infiltration and an elevated level of tumor mutational burden.

CONCLUSION

An 11-gene model was constructed based on CAF-related genes to predict LUAD prognosis. This model represented an independent prognostic factor for LUAD.

Immune checkpoint inhibitors alone or in combination with chemotherapy for treatment of advanced non-small cell lung cancer after first-line platinum-based chemotherapy: A propensity score matching analysis

Background

Immune checkpoint inhibitors (ICIs) have changed the treatment landscape of several cancer types. However, data are lacking with regard to the clinical responsiveness of ICIs in patients with advanced non-small cell lung cancer (NSCLC) after standard first-line chemotherapy. Therefore, we aimed to evaluate the clinical efficacy of ICI alone or in combination with chemotherapy for patients with advanced NSCLC after first-line platinum-based chemotherapy.

Methods

We retrospectively collected patients with confirmed advanced NSCLC who underwent ICI monotherapy or ICI plus chemotherapy after first-line platinum-based chemotherapy between January 2018 and December 2020. A propensity score matching analysis was used to balance baseline characteristics between the two treatment groups. Kaplan-Meier methods and multivariable Cox regressions were used for survival analyses.

Results

Among 832 eligible patients, 222 received ICI monotherapy and 610 received ICI plus chemotherapy. The median overall survival (OS) of patients who received ICI plus chemotherapy was 16.0 months compared with 13.1 months in patients who received ICI monotherapy (HR: 0.64, 95% CI: 0.49-0.85, P = 0.002). After 1:1 propensity score matching, all baseline characteristics were well-balanced between the two treatment groups. Patients who received ICI plus chemotherapy had significantly longer OS than those who received ICI monotherapy (NR vs. 13.1 months, HR: 0.50, 95% CI: 0.34-0.71, P &lt; 0.001). Meanwhile, the median time to treatment discontinuation was 4.4 months in the ICI-chemo group and 3.5 months in the ICI-mono group (HR: 0.72, 95% CI: 0.58-0.89, P = 0.002). The multivariate analysis indicated that treatment regimen was an independent prognostic factor for OS (HR: 0.488, 95% CI: 0.337-0.707, P &lt; 0.001). Moreover, a nomogram that integrated both treatment regimens and clinicopathological factors was created for survival prediction.

Conclusion

Our study indicated that patients with advanced NSCLC who received ICI plus chemotherapy after first-line platinum-based chemotherapy tended to have longer OS than those who received ICI monotherapy. The multivariate analysis showed that treatment regimen was an independent prognostic factor for OS. Future prospective studies are needed to confirm these findings.

Identification of TCR rearrangements specific for genetic alterations in EGFR-mutated non-small cell lung cancer: results from the ADJUVANT-CTONG1104 trial

Tumor response T cells, which have specific T cell receptor (TCR) rearrangements in tumor-infiltrating lymphocytes, determine their ability to interact with the mutation-derived neoantigens presented by antigen-presenting cells. Little is known about the genetic alterations related to specific TCR clones in non-small cell lung cancer (NSCLC) patients who have an epidermal growth factor receptor (EGFR) mutation. In this study, tumor tissues were collected from 101 patients with stage II/III resectable NSCLC with an EGFR mutation (57 patients were treated with gefitinib and 44 were treated with chemotherapy) in the ADJUVANT-CTONG1104 trial for high-throughput TCRβ V region and exome sequencing. Ten clonal TCRs were associated with EGFR exon 19 deletion (del), EGFR exon 21 mutation (L858R), RB1 alteration, TP53 exon 4/5 missense mutation, TP53 nonsense mutation, or copy number gains in NKX2-1 and CDK4. Among the TCRs, there was frequent use of Vβ20-1Jβ2-3 specifically for EGFR exon 19 del or Vβ9Jβ2-1 specifically for EGFR exon 21 mutation (L858R), and these were significantly associated with favorable overall survival (OS) for NSCLC patients harboring EGFR exon 19 del or exon 21 L858R, particularly in the adjuvant gefitinib setting. Moreover, in comparison with the chemotherapy-preferable (CP) group, higher frequencies of Vβ20-1Jβ2-3 and Vβ9Jβ2-1 were found in the highly TKI-preferable (HTP) or TKI-preferable (TP) groups. Altogether, we identified ten TCR rearrangements specific for genetic alterations in NSCLC. Importantly, high abundance Vβ20-1Jβ2-3 or Vβ9Jβ2-1 may be an immune biomarker for guiding adjuvant gefitinib decisions for NSCLC patients harboring EGFR exon 19 del or EGFR exon 21 L858R.

Liquid Biopsy Analysis as a Tool for TKI-Based Treatment in Non-Small Cell Lung Cancer

The treatment of non-small cell lung cancer (NSCLC) has recently evolved with the introduction of targeted therapy based on the use of tyrosine kinase inhibitors (TKIs) in patients with certain gene alterations, including EGFR, ALK, ROS1, BRAF, and MET genes. Molecular targeted therapy based on TKIs has improved clinical outcomes in a large number of NSCLC patients with advanced disease, enabling significantly longer progression-free survival (PFS). Liquid biopsy is an increasingly popular diagnostic tool for treating TKI-based NSCLC. The studies presented in this article show that detection and analysis based on liquid biopsy elements such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), exosomes, and/or tumor-educated platelets (TEPs) can contribute to the appropriate selection and monitoring of targeted therapy in NSCLC patients as complementary to invasive tissue biopsy. The detection of these elements, combined with their molecular analysis (using, e.g., digital PCR (dPCR), next generation sequencing (NGS), shallow whole genome sequencing (sWGS)), enables the detection of mutations, which are required for the TKI treatment. Despite such promising results obtained by many research teams, it is still necessary to carry out prospective studies on a larger group of patients in order to validate these methods before their application in clinical practice.

miR‑491‑3p functions as a tumor suppressor in non‑small cell lung cancer by targeting fibroblast growth factor 5

The present study aimed to identify the function of miR-491-3p in regulating non-small cell lung cancer (NSCLC). Tumor tissues and adjacent normal tissues were collected from 43 patients with NSCLC. A549 and H1299 cells were transfected with microRNA (miR)-491-3p mimic, mimic negative control (NC), miR-491-3p inhibitor, inhibitor NC, pcDNA3.1-FGF5 vector and control vector. Cell counting kit-8 assay and Edu experiments were performed to assess cell viability and proliferation. Matrigel experiment, wound healing assay and flow cytometric analysis were performed to explore cell invasion, migration and apoptosis, respectively. A dual-luciferase reporter experiment was performed to identify the relationship between miR-491-3p and fibroblast growth factor 5 (FGF5). In vivo study was conducted by using nude mice. The miR-491-3p and FGF5 protein expression levels were investigated using reverse transcription-quantitative polymerase chain reaction and western blot analysis. In NSCLC tumor tissues, miR-491-3p was downregulated and FGF5 was upregulated (P<0.01). Low miR-491-3p expression and high FGF5 mRNA expression was associated with poor outcomes in patients, including advanced TNM stage and lymph node metastasis (P<0.05). upregulation of miR-491-3p suppressed viability, proliferation, invasion and migration of NSCLC cells; however, it promoted apoptosis (P<0.01). FGF5 was a target gene for miR-491-3p. miR-491-3p directly inhibited FGF5 expression. upregulation of FGF5 significantly reversed the inhibitory effects of miR-491-3p on malignant phenotypes of NSCLC cells (P<0.01). miR-491-3p overexpression suppressed the in vivo growth of NSCLC. Thus, it was identified that miR-491-3p functions as a tumor suppressor in NSCLC by directly targeting FGF5.

What does radiomics do in PD-L1 blockade therapy of NSCLC patients?

With the in‐depth understanding of programmed cell death 1 ligand 1 (PD‐L1) in non‐small cell lung cancer (NSCLC), PD‐L1 has become a vital immunotherapy target and a significant biomarker. The clinical utility of detecting PD‐L1 by immunohistochemistry or next‐generation sequencing has been written into guidelines. However, the application of these methods is limited in some circumstances where the biopsy size is small or not accessible, or a dynamic monitor is needed. Radiomics can noninvasively, in real‐time, and quantitatively analyze medical images to reflect deeper information about diseases. Since radiomics was proposed in 2012, it has been widely used in disease diagnosis and differential diagnosis, tumor staging and grading, gene and protein phenotype prediction, treatment plan decision‐making, efficacy evaluation, and prognosis prediction. To explore the feasibility of the clinical application of radiomics in predicting PD‐L1 expression, immunotherapy response, and long‐term prognosis, we comprehensively reviewed and summarized recently published works in NSCLC. In conclusion, radiomics is expected to be a companion to the whole immunotherapy process.

Exploration of Novel Immunological Terms in Lung Cancer With Large Populations: Implications for Immunotherapy

Background

Ideal biomarkers to predict the response to immunotherapy in lung cancer are still lacking. Therefore, there is a need to explore effective biomarkers in large populations.

Objective

The objective of this study is to explore novel immunological classifications that are associated with immunotherapy response through the ssGSEA algorithm.

Methods

Six independent lung cancer cohorts were collected for analysis including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the EMBL-EBI database. The ssGSEA algorithm was performed to extract immune terms. Then, TCGA samples were involved as a training group and other cohorts were used as a validation group. After LASSO and Cox regression, prognostic associated immune terms were extracted and an immune-related risk score (IRS) signature was constructed. Furthermore, the association between IRS signature and clinical data, genome features, stemness indices analysis, tumor immune microenvironment, immunotherapy efficiency, and targeted therapy response was also investigated.

Results

A total of 1,997 samples were enrolled in this study including six large lung cancer cohorts. Fifty-four immune terms were calculated through the ssGSEA algorithm in combined cohorts. Then, a nine-immune-term risk score model named IRS signature was established to predict the prognosis in combined cohorts. We classified patients into high-risk and low-risk subgroups according to the cutoff point. Subsequently, analysis of clinical data and genome features indicated that the patients in the high-IRS group tend to have advanced clinical features (clinical stage and T classification), as well as a higher level of copy number variation burden, higher tumor burden mutation, and higher tumor stemness indices. Immune landscape analysis demonstrated that high-IRS groups exhibited lower immune cell infiltration and immune-suppressive state. More importantly, the predicted result of the Tumor Immune Dysfunction and Exclusion analysis showed that high-IRS groups might be more insensitive to immunotherapy. Meanwhile, we have also identified that high-IRS groups were associated with better efficiency of several targeted drugs.

Conclusion

To summarize, we identified a novel IRS model based on nine immune terms, which was quantified by the ssGSEA algorithm. This model had good efficacy in predicting overall survival and immunotherapy response in non-small cell lung cancer patients, which might be an underlying biomarker.

Immune checkpoint inhibitor (ICI)-based treatment beyond progression with prior immunotherapy in patients with stage IV non-small cell lung cancer: a retrospective study

Background

Although immune checkpoint inhibitors (ICIs) provide unprecedented survival improvement for patients with advanced non-small cell lung cancer (NSCLC), disease progression inevitably occurs. After ICIs failure, limited data exist on whether ICI-based treatment beyond progression (TBP) may be beneficial to advanced NSCLC. This retrospective study aimed to evaluate the efficacy of this treatment approach in advanced NSCLC and identify potential beneficial factors.

Methods

Patients with stage IV NSCLC who received ICI-based treatment after the failure of prior PD-1/PD-L1 inhibitor treatments (monotherapy or combination therapy) between January 2016 and July 2020 were enrolled. Their clinical characteristics and treatment procedures were collected, and the follow-up would be performed.

Results

A total of 204 patients were included. All patients had disease progression after prior immunotherapy, with 49.5% (101/204) of patients presenting with new metastasis lesions and the rest 50.5% (103/204) of patients' progression on originate lesions. Within the entire cohort, the median progression-free survival (PFS) and median overall survival (OS) of ICI-based TBP with prior immunotherapy were 5.0 months (95% CI: 4.5-5.5 months) and 15.7 months (95% CI: 14.7-16.8 months), respectively. The objective response rate (ORR) and disease control rate (DCR) were 9.3% and 74.0%, respectively. According to the multivariate analysis, ICI-based combination therapy [PFS: hazard ratio (HR), 0.48, 95% confidence interval (CI): 0.28-0.84, P=0.011] (OS: HR, 0.44, 95% CI: 0.23-0.85, P=0.014), not having targetable gene alterations (PFS: HR, 0.56, 95% CI: 0.40-0.79, P=0.001) (OS: HR, 0.57, 95% CI: 0.37-0.87, P=0.009), and good response to prior immunotherapy (PFS: HR, 0.36, 95% CI: 0.24-0.53, P<0.0001) (OS: HR, 0.31, 95% CI: 0.19-0.52, P<0.0001) were independently associated with improved PFS and OS. Moreover, disease progression due to appearances of new metastasis (OS: HR, 0.56, 95% CI: 0.37-0.84, P=0.005) was only associated with better OS.

Conclusions

While the ORR in patients with advanced NSCLC receiving ICI-based TBP with prior immunotherapy was limited, the DCR was relatively high in our study which is encouraging. ICI-based treatment strategy may be a reasonable option for patients who progressed from prior immunotherapy. Further prospective studies on larger sample size are warranted.

Emerging Blood-Based Biomarkers for Predicting Immunotherapy Response in NSCLC

Simple Summary

Treatment with immunotherapy has been established as a standard treatment for lung cancer in recent years. Unfortunately, still, only a small proportion of patients benefit from the treatment, being the first leading cause of cancer death worldwide. Therefore, there is an urgent need for predictive biomarkers to help clinicians to discern whose patients are more likely to respond to immunotherapy. Since liquid biopsy opens the door to select patients and monitor the response during the treatment in a non-invasive way, in this review, we focus on the most relevant and recent results based on blood soluble biomarkers.

Abstract

Immunotherapy with Immune Checkpoint Inhibitors (ICIs) has demonstrated a profitable performance for Non-Small Cell Lung Cancer (NSCLC) cancer treatment in some patients; however, there is still a percentage of patients in whom immunotherapy does not provide the desired results regarding beneficial outcomes. Therefore, obtaining predictive biomarkers for ICI response will improve the treatment management in clinical practice. In this sense, liquid biopsy appears as a promising method to obtain samples in a minimally invasive and non-biased way. In spite of its evident potential, the use of these circulating biomarkers is still very limited in the real clinical practice, mainly due to the huge heterogeneity among the techniques, the lack of consensus, and the limited number of patients included in these previous studies. In this work, we review the pros and cons of the different proposed biomarkers, such as soluble PD-L1, circulating non-coding RNA, circulating immune cells, peripheral blood cytokines, and ctDNA, obtained from liquid biopsy to predict response to ICI treatment at baseline and to monitor changes in tumor and tumor microenvironment during the course of the treatment in NSCLC patients.

Challenges and the Evolving Landscape of Assessing Blood-Based PD-L1 Expression as a Biomarker for Anti-PD-(L)1 Immunotherapy

While promising, PD-L1 expression on tumor tissues as assessed by immunohistochemistry has been shown to be an imperfect biomarker that only applies to a limited number of cancers, whereas many patients with PD-L1-negative tumors still respond to anti-PD-(L)1 immunotherapy. Recent studies using patient blood samples to assess immunotherapeutic responsiveness suggests a promising approach to the identification of novel and/or improved biomarkers for anti-PD-(L)1 immunotherapy. In this review, we discuss the advances in our evolving understanding of the regulation and function of PD-L1 expression, which is the foundation for developing blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy. We further discuss current knowledge and clinical study results for biomarker identification using PD-L1 expression on tumor and immune cells, exosomes, and soluble forms of PD-L1 in the peripheral blood. Finally, we discuss key challenges for the successful development of the potential use of blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy.

Efficacy and Safety of Gefitinib Plus Anlotinib for Patients with EGFR Positive Advanced Non-Small-Cell Lung Cancer: A Retrospective Exploratory Study

Objective

This study was to investigate the efficacy and safety of gefitinib plus anlotinib for patients with EGFR positive advanced non-small cell lung cancer (NSCLC) in a first-line setting.

Methods

A total of 36 patients with previously-untreated EGFR positive advanced NSCLC were included in this study retrospectively. All patients were administered with gefitinib plus anlotinib combination therapy. The efficacy of the patients was evaluated with the change of target lesion using imaging evidence according to RECIST 1.1 criteria and all the patients were followed up regularly. Adverse reactions were collected and documented during the combination administration. Univariate analysis according to the baseline characteristic subgroup was implemented using Log rank test and multivariate analysis was adjusted by Cox regression analysis.

Results

All the 36 patients included in our study were available for efficacy and safety analysis. Best overall response of the patients during gefitinib plus anlotinib administration suggested that partial response was observed in 30 patients, stable disease was noted in five patients, and progressive disease was found in one patient, which yielded an objective response rate (ORR) of 83.3% (95% CI=67.2–93.6%) and a disease control rate (DCR) of 97.2% (95% CI=85.5–99.9%). Prognostic data indicated that the median progression-free survival (PFS) of the 36 patients with NSCLC was 15.2 months (95% CI=8.15–22.26). Furthermore, the median overall survival (OS) of the 36 patients was 35.9 months (95% CI=22.77–49.03). Additionally, the most common adverse reactions of the patients with NSCLC were diarrhea (63.9%), fatigue (58.3%), hypertension (50.0%), rash (44.4%), and nausea and vomiting (41.7%). Furthermore, ECOG performance status was associated with PFS of gefitinib plus anlotinib combination therapy in baseline characteristic subgroup analysis.

Conclusion

Gefitinib plus anlotinib regimen demonstrated encouraging efficacy and an acceptable safety profile for patients with previously untreated EGFR positive NSCLC preliminarily. The conclusion should be validated in prospective clinical trials subsequently.

Harnessing Liquid Biopsies to Guide Immune Checkpoint Inhibitor Therapy

Immunotherapy (IO), involving the use of immune checkpoint inhibition, achieves improved response-rates and significant disease-free survival for some cancer patients. Despite these beneficial effects, there is poor predictability of response and substantial rates of innate or acquired resistance, resulting in heterogeneous responses among patients. In addition, patients can develop life-threatening adverse events, and while these generally occur in patients that also show a tumor response, these outcomes are not always congruent. Therefore, predicting a response to IO is of paramount importance. Traditionally, tumor tissue analysis has been used for this purpose. However, minimally invasive liquid biopsies that monitor changes in blood or other bodily fluid markers are emerging as a promising cost-effective alternative. Traditional biomarkers have limitations mainly due to difficulty in repeatedly obtaining tumor tissue confounded also by the spatial and temporal heterogeneity of tumours. Liquid biopsy has the potential to circumvent tumor heterogeneity and to help identifying patients who may respond to IO, to monitor the treatment dynamically, as well as to unravel the mechanisms of relapse. We present here a review of the current status of molecular markers for the prediction and monitoring of IO response, focusing on the detection of these markers in liquid biopsies. With the emerging improvements in the field of liquid biopsy, this approach has the capacity to identify IO-eligible patients and provide clinically relevant information to assist with their ongoing disease management.

Research Progress of Anti-PD-1/PD-L1 Immunotherapy Related Mechanisms and Predictive Biomarkers in NSCLC

Programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) is an important pair of immune checkpoints (IC), which play an essential role in the immune escaping process of tumors. Anti-PD-1/PD-L1 immunotherapy can block the suppression effect of the immune system produced by tumor cells through the PD-1/PD-L1 axis and restore the pernicious effect of the immune system on tumor cells. The specific mechanism of anti-PD-1/PD-L1 immunotherapy is closely related to PI3K (phosphatidylinositol 3-kinase)/AKT (AKT serine/threonine kinase 1), JNK (c-Jun N-terminal kinase), NF-kB (nuclear factor-kappa B subunit 1), and other complex signaling pathways. Patients receiving anti-PD-1/PD-L1 immunotherapy are prone to drug resistance. The mechanisms of drug resistance mainly include weakening recognition of tumor antigens by immune cells, inhibiting activation of immune cells, and promoting the production of suppressive immune cells and molecules. Anti-PD-1/PD-L1 immunotherapy plays a vital role in non-small cell lung cancer (NSCLC). It is essential to find better efficacy prediction-related biomarkers and screen patients suitable for immunotherapy. At present, common biomarkers related to predicting immune efficacy mainly include PD-L1 expression level in tumors, tumor mutation burden (TMB), microsatellite instability (MSI)/mismatch repair (MMR), mutations of driver gene, etc. However, the screening efficacy of each indicator is not ideal, and the combined application of multiple indicators is currently used. This article comprehensively reviews anti-PD-1/PD-L1 immunotherapy-related mechanisms, drug resistance-related mechanisms, and therapeutic efficacy-related predictive biomarkers.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing Data to Establish and Validate a Prognostic Model for Patients With Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) remains a lethal disease worldwide, with numerous studies exploring its potential prognostic markers using traditional RNA sequencing (RNA-seq) data. However, it cannot detect the exact cellular and molecular changes in tumor cells. This study aimed to construct a prognostic model for LUAD using single-cell RNA-seq (scRNA-seq) and traditional RNA-seq data.

Methods: Bulk RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) database. LUAD scRNA-seq data were acquired from Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Weighted Gene Correlation Network Analysis (WGCNA) was utilized to identify key modules and differentially expressed genes (DEGs). The non-negative Matrix Factorization (NMF) algorithm was used to identify different subtypes based on DEGs. The Cox regression analysis was used to develop the prognostic model. The characteristics of mutation landscape, immune status, and immune checkpoint inhibitors (ICIs) related genes between different risk groups were also investigated.

Results: scRNA-seq data of four samples were integrated to identify 13 clusters and 9cell types. After applying differential analysis, NK cells, bladder epithelial cells, and bronchial epithelial cells were identified as significant cell types. Overall, 329 DEGs were selected for prognostic model construction through differential analysis and WGCNA. Besides, NMF identified two clusters based on DEGs in the TCGA cohort, with distinct prognosis and immune characteristics being observed. We developed a prognostic model based on the expression levels of six DEGs. A higher risk score was significantly correlated with poor survival outcomes but was associated with a more frequent TP53 mutation rate, higher tumor mutation burden (TMB), and up-regulation of PD-L1. Two independent external validation cohorts were also adopted to verify our results, with consistent results observed in them.

Conclusion: This study constructed and validated a prognostic model for LUAD by integrating 10× scRNA-seq and bulk RNA-seq data. Besides, we observed two distinct subtypes in this population, with different prognosis and immune characteristics.

Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis

Background

The early-stage lung adenocarcinoma (LUAD) rate has increased with heightened public awareness and lung cancer screening implementation. Lipid metabolism abnormalities are associated with lung cancer initiation and progression. However, the comprehensive features and clinical significance of the immunometabolism landscape and lipid metabolism-related genes (LMRGs) in cancer recurrence for early-stage LUAD remain obscure.

Methods

LMRGs were extracted from Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Samples from The Cancer Genome Atlas (TCGA) were used as training cohort, and samples from four Gene Expression Omnibus (GEO) datasets were used as validation cohorts. The LUAD recurrence-associated LMRG molecular pattern and signature was constructed through unsupervised consensus clustering, time-dependent receiver operating characteristic (ROC), and least absolute shrinkage and selection operator (LASSO) analyses. Kaplan-Meier, ROC, and multivariate Cox regression analyses and prognostic meta-analysis were used to test the suitability and stability of the signature. We used Gene Ontology (GO), KEGG pathway, immune cell infiltration, chemotherapy response analyses, gene set variation analysis (GSVA), and GSEA to explore molecular mechanisms and immune landscapes related to the signature and the potential of the signature to predict immunotherapy or chemotherapy response.

Results

First, two LMRG molecular patterns were established, which showed diverse prognoses and immune infiltration statuses. Then, a 12-gene signature was identified, and a risk model was built. The signature remained an independent prognostic parameter in multivariate Cox regression and prognostic meta-analysis. In addition, this signature stratified patients into high- and low-risk groups with significantly different recurrence rates and was well validated in different clinical subgroups and several independent validation cohorts. The results of GO and KEGG analyses and GSEA showed that there were differences in multiple lipid metabolism, immune response, and drug metabolism pathways between the high- and low-risk groups. Further analyses revealed that the signature-based risk model was related to distinct immune cell proportions, immune checkpoint parameters, and immunotherapy and chemotherapy response, consistent with the GO, KEGG, and GSEA results.

Conclusions

This is the first lipid metabolism-based signature for predicting recurrence, and it could provide vital guidance to achieve optimized antitumor for immunotherapy or chemotherapy for early-stage LUAD.

Polymorphonuclear Myeloid-Derived Suppressor Cells Are Abundant in Peripheral Blood of Cancer Patients and Suppress Natural Killer Cell Anti-Tumor Activity

Tumor microenvironment (TME) includes a wide variety of cell types and soluble factors capable of suppressing immune-responses. While the role of NK cells in TME has been analyzed, limited information is available on the presence and the effect of polymorphonuclear (PMN) myeloid-derived suppressor cells, (MDSC). Among the immunomodulatory cells present in TME, MDSC are potentially efficient in counteracting the anti-tumor activity of several effector cells. We show that PMN-MDSC are present in high numbers in the PB of patients with primary or metastatic lung tumor. Their frequency correlated with the overall survival of patients. In addition, it inversely correlated with low frequencies of NK cells both in the PB and in tumor lesions. Moreover, such NK cells displayed an impaired anti-tumor activity, even those isolated from PB. The compromised function of NK cells was consequent to their interaction with PMN-MDSC. Indeed, we show that the expression of major activating NK receptors, the NK cytolytic activity and the cytokine production were inhibited upon co-culture with PMN-MDSC through both cell-to-cell contact and soluble factors. In this context, we show that exosomes derived from PMN-MDSC are responsible of a significant immunosuppressive effect on NK cell-mediated anti-tumor activity. Our data may provide a novel useful tool to implement the tumor immunoscore. Indeed, the detection of PMN-MDSC in the PB may be of prognostic value, providing clues on the presence and extension of both adult and pediatric tumors and information on the efficacy not only of immune response but also of immunotherapy and, possibly, on the clinical outcome.

Clinical outcomes and safety of osimertinib plus anlotinib for patients with previously treated EGFR T790M-positive NSCLC: A retrospective study

WHAT IS KNOWN AND OBJECTIVE

Although osimertinib achieved convincing efficacy for patients with EGFR T790M-positive non-small-cell lung cancer (NSCLC) as second-line treatment in the AURA3 clinical trials, patients developed drug resistance ultimately. Therefore, the present study was to investigate the clinical outcome and safety of osimertinib plus anlotinib for patients with previously treated EGFR T790M-positive NSCLC.

METHODS

Designed as a retrospective study, this study consecutively included a total of 33 patients with advanced NSCLC who possessed a EGFR T790M-positive mutation and progressed after the first-line therapy. Eligible patients were treated with osimertinib plus anlotinib. Baseline characteristics of the patients were collected during hospitalization. Efficacy of the combination regimen was assessed with the change of target lesion using imaging evidence according to RECIST 1.1 criteria, and all the patients were followed up regularly. Adverse reactions were collected and documented during the treatment. Univariate analysis according to baseline characteristic subgroups was performed using log-rank test, and multivariate analysis was carried out by Cox regression analysis.

RESULTS AND DISCUSSION

The best overall response of the patients during osimertinib and anlotinib combination indicated that complete response was found in one patient, partial response was observed in 26 patients, stable disease was noted in 5 patients and progressive disease was reported in one patient. Therefore, objective response rate (ORR) of the combination regimen was 81.8% (95%CI: 64.5%-93.0%), and disease control rate (DCR) was 97.0% (95%CI: 84.2%-99.9%). Furthermore, the median progression-free survival (PFS) of the 33 patients with NSCLC was 15.5 months (95%CI: 6.19-24.81). In addition, the median overall survival (OS) of the 33 patients with NSCLC was 23.8 months (95% CI: 17.67-29.93). Safety profile suggested that the most common adverse reactions of the patients with NSCLC who received anlotinib plus osimertinib were hypertension (63.6%), fatigue (57.6%), diarrhoea (48.5%%), dermal toxicity (39.4%) and proteinuria (33.3%). Interestingly, multivariate Cox regression analysis for PFS demonstrated that ECOG performance status was an independent factor to predict the PFS of the combination regimen.

WHAT IS NEW AND CONCLUSION

Osimertinib plus anlotinib regimen preliminarily exhibited encouraging clinical outcomes and acceptable safety profile for patients with previously treated EGFR T790M-positive NSCLC numerically. This conclusion should be validated in prospective clinical trials.

Identification and Validation of Afatinib Potential Drug Resistance Gene BIRC5 in Non-Small Cell Lung Cancer

Introduction

Resistance to second-generation epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), afatinib, is the most significant challenge in the clinical management of non-small cell lung cancer (NSCLC), and the underlying mechanisms remain unclear.

Methods

Genomic signatures that may confer afatinib resistance in NSCLC were identified via data mining of public databases and integrative bioinformatic analyses. Furthermore, acquired afatinib-resistant lung adenocarcinoma cell lines (HCC827 AR) were established by long-term exposure under afatinib in vitro for stepwise escalation. The expression of baculovirus IAP repeat protein 5 (BIRC5) was detected by western blot, and cellular viability of HCC827 AR was determined by CCK8.

Results

Through integrative bioinformatic analyses of public datasets, overexpression of baculovirus IAP repeat protein 5 (BIRC5) was identified in both afatinib-resistant NSCLC cells and tissues, and BIRC5 overexpression was positively correlated with lymph node metastasis as well as pathological stage in NSCLC. Furthermore, NSCLC patients with BIRC5 overexpression showed poor survival outcomes. Immune infiltration analysis suggested that BIRC5 expression was significantly inversely correlated with tumor-infiltrating cell numbers and immune biomarker expression in NSCLC. The functions of genes co-expressed with BIRC5 were mainly enriched in cell cycle mitotic phase transition, double-strand break repair, and negative regulation of the cell cycle process signaling pathway. In addition, overexpression of BIRC5 protein was detected in afatinib-resistant cells by western blot, while BIRC5-expressing cells treated with BIRC5 inhibitor, YM155, were sensitive to afatinib.

Conclusions

In this study, we showed that overexpression of BIRC5 resulted in resistance to afatinib in NSCLC and BIRC5-specific inhibitors may overcome the resistant phenotype, indicating that dysregulation of the apoptotic cell death pathway may be the key mechanism underlying TKI resistance in the development of NSCLC.

Efficacy and Safety of Anlotinib Monotherapy as Third-Line Therapy for Elderly Patients with Non-Small Cell Lung Cancer: A Real-World Exploratory Study

Purpose

The present study was to investigate the real-world efficacy and safety of anlotinib monotherapy as third-line therapy for elderly patients with advanced non-small cell lung cancer (NSCLC).

Methods

A total of 83 elderly patients (>65 years) with NSCLC who were progressed at least two lines of previous systemic therapy were recruited retrospectively. Patients were treated with anlotinib monotherapy (12 mg or 10 mg). Efficacy of anlotinib was assessed and all the patients were followed up regularly. Adverse reactions were collected during anlotinib administration. Univariate analysis was performed using Log rank test and multivariate analysis was adjusted by Cox regression analysis. Additionally, prognostic analysis according to common adverse reactions was implemented to identify the potential clinical significance.

Results

The best overall response of the 83 elderly patients during anlotinib monotherapy indicated that partial response (PR) was observed in six patients, stable disease (SD) was noted in 59 patients, and progressive disease (PD) was reported in 18 patients. Consequently, the objective response rate (ORR) was 7.2% (95% CI=2.7–15.1%) and the disease control rate (DCR) was 78.3% (95% CI=67.9–86.6%). The median progression-free survival (PFS) of the 83 elderly patients with NSCLC was 4.2 months (95% CI=3.51–4.89). Furthermore, the median overall survival (OS) of the 83 patients was 9.6 months (95% CI=6.65–12.55). The safety profile suggested that the relatively common adverse reactions of the elderly patients with ES-SCLC receiving anlotinib therapy were hypertension (49.4%), fatigue (45.8%), and hand–foot syndrome (39.8%). Interestingly, association analysis exhibited that the median PFS of patients with hypertension and non-hypertension was 4.5 and 3.0 months, respectively (χ²=6.306, P=0.012).

Conclusion

Anlotinib monotherapy demonstrated a satisfactory efficacy and tolerable safety profile in third-line settings for elderly patients with advanced NSCLC. Patients who experienced a hypertension adverse reaction induced by anlotinib therapy might confer superior PFS. The conclusion should be validated in prospective clinical trials subsequently.