TP53, STK11, and EGFR Mutations Predict Tumor Immune Profile and the Response to Anti-PD-1 in Lung Adenocarcinoma

Evaluating distinct KRAS subtypes as potential biomarkers for immune checkpoint inhibitor efficacy in lung adenocarcinoma

Background

Despite the acknowledged predictive value of KRAS in immune checkpoint inhibitor (ICI) responses, the heterogeneous behavior of its mutations in this sphere remains largely unexplored. As of now, no studies have definitively categorized KRAS subtype variations as independent prognostic indicators for ICI responses in lung cancer patients.

Methods

We analyzed a cohort of 103 patients, all harboring different KRAS mutation subtypes, and complemented this data with information from TCGA and GEO databases. Our research focused on delineating the relationships between KRAS mutation subtypes and factors like immunotherapy markers and immune cell composition, in addition to examining survival rates, drug sensitivity, and PD-L1 responses corresponding to distinct KRAS subtypes.

Results

We found that the G12V and G12D subtypes demonstrated elevated expressions of immunotherapy markers, implying a potentially enhanced benefit from immunotherapy. Significant variations were identified in the distribution of naive B cells, activated CD4+ memory T cells, and regulatory T cells (Tregs) across different KRAS mutant subtypes. A notable difference was observed in the Tumor Mutation Burden (TMB) levels across the four KRAS subtypes, with the G12D subtype displaying the lowest TMB level. Furthermore, G12C subtype showcased the worst prognosis in terms of progression-free intervals (PFI), in stark contrast to the more favorable outcomes associated with the G12A subtype.

Conclusion

Our study reveals that KRAS mutations exhibit considerable variability in predicting outcomes for LUAD patients undergoing ICI treatment. Thus, the evaluation of KRAS as a biomarker for ICIs necessitates recognizing the potential diversity inherent in KRAS mutations.

Pembrolizumab combined with anlotinib improves therapeutic efficacy in pulmonary sarcomatoid carcinoma with TMB-H and PD-L1 expression: a case report and literature review

Background

Pulmonary sarcomatoid carcinoma (PSC) is a unique subtype of non-small cell lung cancer (NSCLC) with a high degree of malignancy and poor therapeutic effects. With the widespread use of immune checkpoint inhibitors (ICIs) in recent years, few studies have reported that immunotherapy is effective against PSC. As a multi-target anti-vascular targeting agent, anlotinib showed a better anti-tumor effect in various cancer species. The paper reported the therapeutic and side effects of pembrolizumab combined with anlotinib in a patient with advanced PSC.

Case presentation

This is a 73 year old female patient who underwent thoracoscopy right upper lobectomy and was diagnosed as locally advanced PSC. However, the patient experienced tumor recurrence and metastasis 7 weeks after surgery and was unable to tolerate chemoradiotherapy. Moreover, she detected TP53 mutation and found that tumor mutation burden (TMB) and PD-L1 were high expression. Therefore, the patient received pembrolizumab combined with anlotinib treatment. After 15 cycles of treatment, the tumor significantly shrank with no tumor activity. The evaluation of tumor efficacy is partial response (PR). During the treatment period, she experienced one-degree thyroid-stimulating hormone elevation and two-degree hand-foot syndrome. Pembrolizumab and anlotinib was continued for two years as a maintenance treatment. The patient had a good quality of life and no disease progression was observed. Currently, the patient is still alive without tumor progression and has overall survival exceeding 45 months and toxic side effects were tolerable.

Conclusions

Combining ICIs and anti-angiogenic targeted therapy has brought new hope in treating advanced PSC. Additionally, TMB and PD-L1 expression could be potential predictive biomarkers of the efficacy in advanced PSC with immunotherapy.

Cancer cell-intrinsic mechanisms driving acquired immune tolerance

Immune evasion is a hallmark of cancer, enabling tumors to survive contact with the host immune system and evade the cycle of immune recognition and destruction. Here, we review the current understanding of the cancer cell-intrinsic factors driving immune evasion. We focus on T cells as key effectors of anti-cancer immunity and argue that cancer cells evade immune destruction by gaining control over pathways that usually serve to maintain physiological tolerance to self. Using this framework, we place recent mechanistic advances in the understanding of cancer immune evasion into broad categories of control over T cell localization, antigen recognition, and acquisition of optimal effector function. We discuss the redundancy in the pathways involved and identify knowledge gaps that must be overcome to better target immune evasion, including the need for better, routinely available tools that incorporate the growing understanding of evasion mechanisms to stratify patients for therapy and trials.

Correlation Analysis of the TP53 Mutation With Clinical Characteristics in the Prognosis of Non-Small Cell Lung Cancer

Background

Non-small cell lung cancer (NSCLC) with TP53 mutations has a worse prognosis. It was generally more resistant to chemotherapy and radiation. Our aim was to investigate the correlation between the TP53 co-mutated gene and clinical features, and prognostic value in patients with NSCLC.

Methods

Seventy-three patients with a diagnosis of NSCLC at our hospital were recruited. They were divided into the TP53 mutation status (minor) (TP53 MU) and TP53 wild-type (major) (TP53 WT) groups according to their clinical characteristics after their mutation data and clinical information were collected. Serum markers were compared between groups using Mann-Whitney U test. Other clinical factors were compared between groups using χ2 test and Fisher exact test. The log-rank test was used to compare survival curves.

Results

Of the 73 patients with NSCLC, 37 (50.68%) were found to carry TP53 mutation. TP53 MU and TP53 WT groups (n = 36) showed a significant difference in the number of smokers, incidence of squamous cell carcinoma, EGFR mutation, and number of advanced patients (P < .05), while gender, age, lymph node metastasis, and KRAS mutation did not differ significantly between the 2 groups. The survival curves in the TP53/KRAS and the TP53/EGFR co-mutation groups suggest that patients with NSCLC may have a shorter progression-free survival (PFS) if they carry one of the 2 types of co-mutation.

Conclusions

TP53 gene mutations are more common in patients with NSCLC and squamous cell carcinoma. New predictive markers for NSCLC prognosis may be TP53/KRAS and TP53/EGFR co-mutations.

Comparative bioinformatic analysis of KRAS, STK11 and KEAP1 (co-)mutations in non-small cell lung cancer with a special focus on KRAS G12C

OBJECTIVES

Mutations in STK11 (STK11MUT) and KEAP1 (KEAP1MUT) occur frequently in non-small cell lung cancer (NSCLC) and are often co-mutated with KRAS. Several studies linked the co-occurrence of KRASMUT + STK11MUT, as well as KRASMUT + KEAP1MUT to reduced response to immune checkpoint inhibitors (ICI) and even a negative impact on survival. Data focusing STK11 + KEAP1 co-mutations or the triple mutation (KRAS + STK11 + KEAP1) are scarce. The recent availability of KRAS-G12C inhibitors increases the clinical relevance of those co-mutations in KRAS-mutated NSCLC.

MATERIALS AND METHODS

We present a comprehensive bioinformatic analysis encompassing six datasets retrieved from cBioPortal.

RESULTS

Independent of the treatment, triple mutations and STK11MUT + KEAP1MUT were significantly associated with a reduced overall survival (OS). Across treatments, OS of patients with a KRAS G12C triple mutation was significantly reduced compared to patients with KRAS G12C-only. Under ICI-therapy, there was no significant difference in OS between patients harboring the KRAS G12C-only and patients with the KRAS G12C triple mutation, but a significant difference between patients harboring KRAS non-G12C and KRAS non-G12C triple mutations. Triple mutated primary tumors showed a significantly increased frequency of distant metastases to bone and adrenal glands compared to KRAS-only mutated tumors. Additionally, our drug response analysis in cancer cell lines harboring the triple mutations revealed the WNT pathway inhibitor XAV-939 as a potential future drug candidate for this mutational situation.

CONCLUSION

The triple mutation status may serve as a negative prognostic and predictive factor across treatments compared to KRASMUT-only. KRAS G12C generally seems to be a negative predictive marker for ICI-therapy.

Tumor-intrinsic metabolic reprogramming and how it drives resistance to anti-PD-1/PD-L1 treatment

The development of immune checkpoint blockade (ICB) therapies has been instrumental in advancing the field of immunotherapy. Despite the prominence of these treatments, many patients exhibit primary or acquired resistance, rendering them ineffective. For example, anti-programmed cell death protein 1 (anti-PD-1)/anti-programmed cell death ligand 1 (anti-PD-L1) treatments are widely utilized across a range of cancer indications, but the response rate is only 10%-30%. As such, it is necessary for researchers to identify targets and develop drugs that can be used in combination with existing ICB therapies to overcome resistance. The intersection of cancer, metabolism, and the immune system has gained considerable traction in recent years as a way to comprehensively study the mechanisms that drive oncogenesis, immune evasion, and immunotherapy resistance. As a result, new research is continuously emerging in support of targeting metabolic pathways as an adjuvant to ICB to boost patient response and overcome resistance. Due to the plethora of studies in recent years highlighting this notion, this review will integrate the relevant articles that demonstrate how tumor-derived alterations in energy, amino acid, and lipid metabolism dysregulate anti-tumor immune responses and drive resistance to anti-PD-1/PD-L1 therapy.

Comprehensive analysis of PILRΑ's association with the prognosis, tumor immune infiltration, and immunotherapy in pan-cancer

Paired immunoglobulin-like type 2 receptor alpha (PILRA) plays a vital role in regulating broad immune responses. However, the roles of PILRA in cancer immunity remain unexplored yet. In the current study, we comprehensively analyzed the oncogenic and immunologic roles of PILRA at a pan-cancer level based on the Cancer Genome Atlas and Gene Expression Omnibus datasets. PILRA was significantly dysregulated and frequently mutated in pan-cancer. Its expression and mutation status significantly impacted patient prognosis in several cancers. Besides, PILRA expression was positively correlated with ESTIMATE scores and the abundances of tumor-infiltrating immune cells. Concurrently, PILRA expression was significantly associated with predictive biomarkers of cancer immunotherapy, and positively correlated with the prognostic outcomes of cancer patients receiving immunotherapy. Mechanistically, enrichment analysis implied that PILRA might be involved in the regulation of immune response and metabolic process. This study uncovered the immunological roles of PILRA in cancers and its potential as a novel biomarker and therapeutic target for cancer immunotherapy.

SART3, regulated by p53, is a biomarker for diagnosis, prognosis and immune infiltration in hepatocellular carcinoma

OBJECTIVE

This study aimed to investigate the role of squamous cell carcinoma antigen recognized by T cells 3 (SART3) in hepatocellular carcinoma (HCC).

METHODS

SART3 expression and prognostic value were analyzed in TCGA and GEO datasets. The diagnostic value and prognostic significance of SART3 were determined using immunohistochemistry in the Guangxi cohort. The whole-exome mutation spectrum of SART3 was analyzed in high and low expression groups in both TCGA and Guangxi cohorts. The biological functions of the SART3 gene were validated through in vitro experiments using small interfering RNA technology to downregulate SART3 expression in HCC cell lines.

RESULTS

SART3 expression was significantly higher in HCC tissues than in adjacent noncancerous liver tissues in TCGA, GEO and Guangxi cohorts. High expression of SART3 was significantly associated with poor prognosis in HCC patients. In TCGA and Guangxi cohorts, the expression of SART3 in the TP53 mutation group was significantly higher than that in the non-mutation group. Downregulation of SART3 expression significantly inhibited the migration and proliferation of HCC cells. SART3 may be involved mainly in immune infiltration of Th2 cells and macrophages in HCC. Additionally, SART3 can upregulate the expression of immune checkpoints (PD-L1 and TIM-3) and predict potential therapeutic agents for HCC.

CONCLUSION

The findings of this study demonstrate the diagnostic and prognostic value of SART3 in HCC. SART3 may be associated with immune infiltration of Th2 cells and macrophages in HCC, highlighting its potential role in the development and progression of HCC.

Biomarkers for immune checkpoint inhibition in sarcomas - are we close to clinical implementation?

Sarcomas are a group of diverse and complex cancers of mesenchymal origin that remains poorly understood. Recent developments in cancer immunotherapy have demonstrated a potential for better outcomes with immune checkpoint inhibition in some sarcomas compared to conventional chemotherapy. Immune checkpoint inhibitors (ICIs) are key agents in cancer immunotherapy, demonstrating improved outcomes in many tumor types. However, most patients with sarcoma do not benefit from treatment, highlighting the need for identification and development of predictive biomarkers for response to ICIs. In this review, we first discuss United States (US) Food and Drug Administration (FDA)-approved and European Medicines Agency (EMA)-approved biomarkers, as well as the limitations of their use in sarcomas. We then review eight potential predictive biomarkers and rationalize their utility in sarcomas. These include gene expression signatures (GES), circulating neutrophil-to-lymphocyte ratio (NLR), indoleamine 2,3-dioxygenase (IDO), lymphocyte activation gene 3 (LAG-3), T cell immunoglobin and mucin domain-containing protein 3 (TIM-3), TP53 mutation status, B cells, and tertiary lymphoid structures (TLS). Finally, we discuss the potential for TLS as both a predictive and prognostic biomarker for ICI response in sarcomas to be implemented in the clinic.

PTPRD mutation is a prognostic biomarker for sensitivity to ICIs treatment in advanced non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC). ICIs can provide durable responses and prolong survival for some patients. With the increasing routine of next-generation sequencing (NGS) in clinical practice, it is essential to integrate prognostic factors to establish novel nomograms to improve clinical prediction ability in NSCLC with ICIs treatment.

METHODS

Clinical information, response data, and genome data of advanced NSCLC treated ICIs were obtained from cBioPortal. The top 20 gene alterations in durable clinical benefit (DCB) were compared with those genes in no durable benefit (NDB). Survival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram.

RESULTS

The mutation of PTPRD was significantly related to progression free survival (PFS) and overall survival (OS) in advanced NSCLC with ICIs treatment (PFS: p = 0.0441, OS: p = 0.0086). The PTPRD mutation was closely related to tumor mutational burden (TMB) and tumor-infiltrating immune cells (TIICs). Two novel nomograms were built to predict the PFS and OS of advanced NSCLC patients with ICIs treatment.

CONCLUSIONS

Our study suggested that PTPRD mutations could serve as a predictive biomarker for the sensitivity to ICIs treatment and PFS and OS in advanced NSCLC with ICIs. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS for advanced NSCLC patients with ICIs.

The role of p53 in anti-tumor immunity and response to immunotherapy

p53 is a transcription factor that regulates the expression of genes involved in tumor suppression. p53 mutations mediate tumorigenesis and occur in approximately 50% of human cancers. p53 regulates hundreds of target genes that induce various cell fates including apoptosis, cell cycle arrest, and DNA damage repair. p53 also plays an important role in anti-tumor immunity by regulating TRAIL, DR5, TLRs, Fas, PKR, ULBP1/2, and CCL2; T-cell inhibitory ligand PD-L1; pro-inflammatory cytokines; immune cell activation state; and antigen presentation. Genetic alteration of p53 can contribute to immune evasion by influencing immune cell recruitment to the tumor, cytokine secretion in the TME, and inflammatory signaling pathways. In some contexts, p53 mutations increase neoantigen load which improves response to immune checkpoint inhibition. Therapeutic restoration of mutated p53 can restore anti-cancer immune cell infiltration and ameliorate pro-tumor signaling to induce tumor regression. Indeed, there is clinical evidence to suggest that restoring p53 can induce an anti-cancer immune response in immunologically cold tumors. Clinical trials investigating the combination of p53-restoring compounds or p53-based vaccines with immunotherapy have demonstrated anti-tumor immune activation and tumor regression with heterogeneity across cancer type. In this Review, we discuss the impact of wild-type and mutant p53 on the anti-tumor immune response, outline clinical progress as far as activating p53 to induce an immune response across a variety of cancer types, and highlight open questions limiting effective clinical translation.

Identification and validation of Birc5 as a novel activated cell cycle program biomarker associated with infiltration of immunosuppressive myeloid-derived suppressor cells in hepatocellular carcinoma

BACKGROUND

Preclinical studies and clinical trials have demonstrated that tumor-intrinsic activation of the cell cycle program impedes anticancer immunotherapy. Identification of cell cycle-related biomarkers may provide novel therapeutic targets to augment the efficacy of immunotherapy in hepatocellular carcinoma (HCC).

METHOD AND RESULTS

Based on the genes related to cell cycle program, two clusters (Cluster 1 and Cluster 2) were detected in HCC patients via non-negative matrix factorization algorithm. Multivariable-adjusted Cox regression analysis indicated that the cell cycle gene-based classification was a significant prognostic factor for predicting the clinical outcome of HCC patients. Cluster 1 showed shorter overall survival time and progression-free interval time was associated with activated cell cycle program, higher infiltration of myeloid-derived suppressor cells (MDSCs) and less sensitivity to immunotherapy. A three-gene prognostic model, including BIRC5, C8G, and SPP1, was constructed to characterize the cell cycle-based classification of HCC, which had strong robustness and a stable predictive performance. Notably, Birc5 was positively correlated with CD11b expression (a MDSC marker) in HCC tissue. Concordant high expression of Birc5 and intratumor infiltration level of MDSCs were correlated with worse prognosis of HCC patients. In vitro, hepatocellular Birc5 overexpression promoted immunosuppressive CD11b+ CD33+ HLA-DR- MDSC expansion from human peripheral blood mononuclear cells. Genetically modified animal model of liver cancer revealed that Birc5 depletion upregulated the genes related to lymphocyte-mediated immunity, natural killer cell-mediated immunity, interferon-gamma production, T-cell activation, and T-cell-mediated cytotoxicity. These results suggest an immunosuppressive function of Birc5 in HCC.

CONCLUSION

Birc5 was a potential biomarker and inducer of intratumor infiltration of MDSCs, which led to T cell exclusion or dysfunction in tumor immune microenvironment, consequently resulting in reduced response to ICIs in HCC.

Case Report: Successful treatment of advanced hepatocarcinoma with the PD-1 inhibitor Camrelizumab

Primary liver cancer is characterized by closely related with chronic liver inflammation, thereby reversing hypoxic immunosuppressive microenvironment of tumor cell growth by immunotherapy drug is a potentially effective strategy. Camrelizumab is an anti-PD-1 antibody being developed by Jiangsu Hengrui Pharmaceuticals Co., Ltd. We reported a case of an adult critical Chinese patient with primary hepatocellular carcinoma and lung metastasis completely responding to Camrelizumab, most of the lesions were stable and no new lesions occurred after 1-year treatment, which provides us to reconsider the therapeutic effect of Camrelizumab on such patients. Camrelizumab had a safety profile for the patient in our case report, except for the occurrence of RCCEP. This case provides the evidence of the effective antitumor activity and manageable toxicities of Camrelizumab for patients with advanced hepatocellular carcinoma, which was the first application as far as we know.

Combined SERS Microfluidic Chip with Gold Nanocone Array for Effective Early Lung Cancer Prognosis in Mice Model

Introduction

As the most common malignant tumor in the world, the prognosis of patients with advanced lung cancer remains poor even after treatment. There are many prognostic marker assays available, but there is still more room for the development of high-throughput and sensitive detection of circulating tumor DNA (ctDNA). Surface-enhanced Raman spectroscopy (SERS), a spectroscopic detection method that has received wide attention in recent years, can achieve exponential amplification of Raman signals by using different metallic nanomaterials. Integrating SERS with signal amplification strategy into the microfluidic chip and applying it to ctDNA detection is expected to be an effective tool for the prognosis of lung cancer treatment effect in the future.

Methods

To construct a high-throughput SERS microfluidic chip integrated with enzyme-assisted signal amplification (EASA) and catalytic hairpin self-assembly (CHA) signal amplification strategies, using hpDNA-functionalized Au nanocone arrays (AuNCAs) as capture substrates and cisplatin-treated lung cancer mice to simulate the detection environment for sensitive detection of ctDNA in serum of lung cancer patients after treatment.

Results

The SERS microfluidic chip constructed by this scheme, with two reaction zones, can simultaneously and sensitively detect the concentrations of four prognostic ctDNAs in the serum of three lung cancer patients with a limit of detection (LOD) as low as the aM level. The results of the ELISA assay are consistent with this scheme, and its accuracy is guaranteed.

Conclusion

This high-throughput SERS microfluidic chip has high sensitivity and specificity in the detection of ctDNA. This could be a potential tool for prognostic assessment of lung cancer treatment efficacy in future clinical applications.

A Critical Review of the Prognostic and Predictive Implications of KRAS and STK11 Mutations and Co-Mutations in Metastatic Non-Small Lung Cancer

The Kirsten rat sarcoma viral oncogene homolog (KRAS) and serine/threonine kinase 11 (STK11) co-mutations are associated with the diverse phenotypic and heterogeneous oncogenic subtypes in non-small cell lung cancer (NSCLC). Due to extensive mixed evidence, there needs to be a review of the recent KRAS and STK11 mutation literature to better understand the potential clinical applications of these genomic biomarkers in the current treatment landscape. This critical review highlights the clinical studies that have elucidated the potential prognostic and predictive implications of KRAS mutations, STK11 mutations, or KRAS/STK11 co-mutations when treating metastatic NSCLC across various types of treatments (e.g., immune checkpoint inhibitors [ICIs]). Overall, KRAS mutations are associated with poor prognoses and have been determined to be a valid but weak prognostic biomarker among patients diagnosed with NSCLC. KRAS mutations in NSCLC have shown mixed results as a predictive clinical biomarker for immune checkpoint inhibitor treatment. Overall, the studies in this review demonstrate that STK11 mutations are prognostic and show mixed results as predictive biomarkers for ICI therapy. However, KRAS/STK11 co-mutations may predict primary resistance to ICI. Prospective KRAS/STK11-biomarker-driven randomized trials are needed to assess the predictive effect of various treatments on the outcomes for patients with metastatic NSCLC, as the majority of the published KRAS analyses are retrospective and hypothesis-generating in nature.

Cancer Cell-Intrinsic Alterations Associated with an Immunosuppressive Tumor Microenvironment and Resistance to Immunotherapy in Lung Cancer

Despite the great clinical success of immunotherapy in lung cancer patients, only a small percentage of them (<40%) will benefit from this therapy alone or combined with other strategies. Cancer cell-intrinsic and cell-extrinsic mechanisms have been associated with a lack of response to immunotherapy. The present study is focused on cancer cell-intrinsic genetic, epigenetic, transcriptomic and metabolic alterations that reshape the tumor microenvironment (TME) and determine response or refractoriness to immune checkpoint inhibitors (ICIs). Mutations in KRAS, SKT11(LKB1), KEAP1 and TP53 and co-mutations of these genes are the main determinants of ICI response in non-small-cell lung cancer (NSCLC) patients. Recent insights into metabolic changes in cancer cells that impose restrictions on cytotoxic T cells and the efficacy of ICIs indicate that targeting such metabolic restrictions may favor therapeutic responses. Other emerging pathways for therapeutic interventions include epigenetic modulators and DNA damage repair (DDR) pathways, especially in small-cell lung cancer (SCLC). Therefore, the many potential pathways for enhancing the effect of ICIs suggest that, in a few years, we will have much more personalized medicine for lung cancer patients treated with immunotherapy. Such strategies could include vaccines and chimeric antigen receptor (CAR) cells.

Bevacizumab/PD-1 inhibitor plus chemotherapy as first-line treatment of advanced non-squamous non-small-cell lung cancer

Aim: To compare the effectiveness of PD-1 inhibitor or bevacizumab plus chemotherapy in advanced non-squamous non-small cell lung cancer (nsNSCLC). Methods: We retrospectively collected data for patients with advanced nsNSCLC who underwent first-line treatment with PD-1 inhibitor or bevacizumab plus chemotherapy (IC and BC groups). Propensity score matching (PSM) was adopted to balance covariates. Results: 278 patients were enrolled, after PSM (n = 104/group), the objective response rate was 45.1% and 24.0% in the IC and BC groups (p = 0.001). Median progression-free survival (PFS) was 13.5 and 8.2 months (p = 0.007), and duration of response was 14.8 versus 8.1 months (p = 0.007), respectively. In subgroup analysis, the PFS for those patients with PD-L1≥1% (16.2 vs 6.8 months, p = 0.000) was significantly longer in the IC group than that in BC group, but not in the PD-L1<1% subgroup (8.9 vs12.7 months, p = 0.719). Conclusion: PD-1 inhibitor plus chemotherapy was superior to bevacizumab plus chemotherapy as first-line treatment for advanced nsNSCLC, which is debatable for patients with PD-L1<1%.

Spatial profiling of the microenvironment reveals low intratumoral heterogeneity and STK11-associated immune evasion in therapy-naïve lung adenocarcinomas

OBJECTIVE

Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting.

MATERIALS AND METHODS

We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype). For each sample the expression of 770 immunooncology-related genes was analyzed using the nCounter platform, while the mutational status was determined by hybrid capture-based next-generation sequencing (NGS) using a large panel covering more than 500 genes.

RESULTS

Global unsupervised analyses revealed clustering of the samples into two groups corresponding to a 'hot' or 'cold' immunologic tumor contexture based on the abundance of immune cell infiltrates. All analyzed specific immune cell signatures (ICsig) showed a significantly higher intertumoral than intratumoral heterogeneity (p < 0.02), as most of the analyzed cases (14/19) showed a very homogenous spatial immune cell profile. PD-L1 exhibited a significantly higher intertumoral than intratumoral heterogeneity (p = 1.03e-13). We found a specific association with 'cold' TME for STK11 (11/14, p < 0.07), but not KRAS, TP53, LRP1B, MTOR, U2AF1 co-mutations, and validated this finding using The Cancer Genome Atlas (TCGA) data.

CONCLUSION

Early-stage lung adenocarcinomas show considerable intertumoral, but limited intratumoral heterogeneity, which is clinically highly relevant as assessment before neoadjuvant treatment is based on small biopsies. STK11 mutations are specifically associated with a 'cold' TME, which could affect the efficacy of perioperative immunotherapy.

Prognostic and Predictive Biomarkers in the Era of Immunotherapy for Lung Cancer

The therapeutic algorithm of lung cancer has recently been revolutionized by the emergence of immune checkpoint inhibitors. However, an objective and durable response rate remains low with those recent therapies and some patients even experience severe adverse events. Prognostic and predictive biomarkers are therefore needed in order to select patients who will respond. Nowadays, the only validated biomarker is the PD-L1 expression, but its predictive value remains imperfect, and it does not offer any certainty of a sustained response to treatment. With recent progresses in molecular biology, genome sequencing techniques, and the understanding of the immune microenvironment of the tumor and its host, new molecular features have been highlighted. There are evidence in favor of the positive predictive value of the tumor mutational burden, as an example. From the expression of molecular interactions within tumor cells to biomarkers circulating in peripheral blood, many markers have been identified as associated with the response to immunotherapy. In this review, we would like to summarize the latest knowledge about predictive and prognostic biomarkers of immune checkpoint inhibitors efficacy in order to go further in the field of precision immuno-oncology.

Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis

BACKGROUND

The TP53 tumor suppressor gene is one of the most mutated genes in lung adenocarcinoma (LUAD) and plays a vital role in regulating the occurrence and progression of cancer. We aimed to elucidate the association between TP53 mutations, response to immunotherapies and the prognosis of LUAD.

METHODS

Genomic, transcriptomic, and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) dataset. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA). Gene set variation analysis (GSVA) were performed to determine the differences in biological pathways. A merged protein-protein interaction (PPI) network was constructed and analyzed. MSIpred was used to analyze the correlation between the expression of the TP53 gene, tumor mutation burden (TMB) and tumor microsatellite instability (MSI). CIBERSORT was used to calculate the abundance of immune cells. Univariate and multivariate Cox regression analyses were used to determine the prognostic value of TP53 mutations in LUAD.

RESULTS

TP53 was the most frequently mutated in LUAD, with a mutational frequency of 48%. GO and KEGG enrichment analysis, GSEA, and GSVA results showed a significant upregulation of several signaling pathways, including PI3K-AKT mTOR (P < 0.05), Notch (P < 0.05), E2F target (NES = 1.8, P < 0.05), and G2M checkpoint (NES = 1.7, P < 0.05). Moreover, we found a significant correlation between T cells, plasma cells, and TP53 mutations (R² < 0.01, P = 0.040). Univariate and multivariate Cox regression analyses revealed that the survival prognosis of LUAD patients was related to TP53 mutations (Hazard Ratio (HR) = 0.72 [95% CI, 0.53 to 0.98], P < 0.05), cancer status (P < 0.05), and treatment outcomes (P < 0.05). Lastly, the Cox regression models showed that TP53 exhibited good power in predicting three- and five-year survival rates.

CONCLUSIONS

TP53 may be an independent predictor of response to immunotherapy in LUAD, and patients with TP53 mutations have higher immunogenicity and immune cell infiltration.

Therapeutic targeting of tumour myeloid cells

Myeloid cells are pivotal within the immunosuppressive tumour microenvironment. The accumulation of tumour-modified myeloid cells derived from monocytes or neutrophils - termed 'myeloid-derived suppressor cells' - and tumour-associated macrophages is associated with poor outcome and resistance to treatments such as chemotherapy and immune checkpoint inhibitors. Unfortunately, there has been little success in large-scale clinical trials of myeloid cell modulators, and only a few distinct strategies have been used to target suppressive myeloid cells clinically so far. Preclinical and translational studies have now elucidated specific functions for different myeloid cell subpopulations within the tumour microenvironment, revealing context-specific roles of different myeloid cell populations in disease progression and influencing response to therapy. To improve the success of myeloid cell-targeted therapies, it will be important to target tumour types and patient subsets in which myeloid cells represent the dominant driver of therapy resistance, as well as to determine the most efficacious treatment regimens and combination partners. This Review discusses what we can learn from work with the first generation of myeloid modulators and highlights recent developments in modelling context-specific roles for different myeloid cell subtypes, which can ultimately inform how to drive more successful clinical trials.

Construction of an STK11 Mutation and Immune-Related Prognostic Prediction Model in Lung Adenocarcinoma

Background

STK11 mutation in LUAD affects immune cell infiltration in tumor tissue, and is associated with tumor prognosis.

Objective

This study aimed to construct a STK11 mutation and immune-related LUAD prognostic model.

Materials and Methods

The mutation frequency of STK11 in LUAD was queried via cBioPortal in TCGA and PanCancer Atlas databases. The degree of immune infiltration was analyzed by CIBERSORT analysis. DEGs in STK11mut and STK11wt samples were analyzed. Metascape, GO and KEGG methods were adopted for functional and signaling pathway enrichment analysis of DEGs. Genes related to immune were overlapped with DEGs to acquire immune-related DEGs, whose Cox regression and LASSO analyses were employed to construct prognostic model. Univariate and multivariate Cox regression analyses verified the independence of riskscore and clinical features. A nomogram was established to predict the OS of patients. Additionally, TIMER was introduced to analyze relationship between infiltration abundance of 6 immune cells and expression of feature genes in LUAD.

Results

The mutation frequency of STK11 in LUAD was 16%, and the degrees of immune cell infiltration were different between the wild-type and mutant STK11. DEGs of STK11 mutated and unmutated LUAD samples were mainly enriched in immune-related biological functions and signaling pathways. Finally, 6 feature genes were obtained, and a prognostic model was established. Riskscore was an independent immuno-related prognostic factor for LUAD. The nomogram diagram was reliable.

Conclusion

Collectively, genes related to STK11 mutation and immunity were mined from the public database, and a 6-gene prognostic prediction signature was generated.

The effects of the prognostic biomarker SAAL1 on cancer growth and its association with the immune microenvironment in lung adenocarcinoma

BACKGROUND

Inhibition of Serum Amyloid A-like 1 (SAAL1) expression could inhibit cancer progression and improve the prognosis of cancer patients. At present, the correlation between SAAL1 and lung adenocarcinoma (LAC) remains unclear. Therefore, this study surveyed the worth and pathway of SAAL1 in LAC progression and immunity.

METHODS

Bioinformatics and immunohistochemistry were used to identify the SAAL1 expression in LAC. The roles of SAAL1 expression in the existence values of LAC patients were explored, and the nomograms were constructed. Clinical values of SAAL1 co-expressed genes were evaluated by COX regression, survival, and Receiver operating characteristic (ROC) analysis. EDU and western blotting methods were used to inquiry the functions and pathways of the SAAL1 in cell growths. The correlation between the SAAL1 level and immune microenvironment was visualized using correlation research.

RESULTS

SAAL1 level was elevated in LAC tissues, and was observed in cancer tissues of dead patients. SAAL1 overexpression had something to do with shorter overall survival, progression-free interval, and disease-specific survival in LAC. The area under the curve of SAAL1 was 0.902 in normal tissues and cancer tissues. Inhibition of SAAL1 expression could inhibit cancer cell proliferation, which may be related to the decreased expression of cyclin D1 and Bcl-2 proteins. In LAC, SAAL1 level had something to do with stromal, immune, and estimate scores, and correlated with macrophages, T cells, Th2 cells, CD8 T cells, NK CD56dim cells, DC, eosinophils, NK CD56bright cells, pDC, iDC, cytotoxic cells, Tgd, aDC cells, B cells, Tcm, and TFH levels. SAAL1 overexpression had something to do with existence values and the immunity in LAC.

CONCLUSIONS

Inhibition of SAAL1 expression could regulate cancer growth via cyclin D1 and Bcl-2. SAAL1 is a promising prognostic biomarker in LAC patients.

Efficacy of immunotherapy in oncogene-driven non-small-cell lung cancer

For advanced metastatic non-small-lung cancer, the landscape of actionable driver alterations is rapidly growing, with nine targetable oncogenes and seven approvals within the last 5 years. This accelerated drug development has expanded the reach of targeted therapies, and it may soon be that a majority of patients with lung adenocarcinoma will be eligible for a targeted therapy during their treatment course. With these emerging therapeutic options, it is important to understand the existing data on immune checkpoint inhibitors (ICIs), along with their efficacy and safety for each oncogene-driven lung cancer, to best guide the selection and sequencing of various therapeutic options. This article reviews the clinical data on ICIs for each of the driver oncogene defined lung cancer subtypes, including efficacy, both for ICI as monotherapy or in combination with chemotherapy or radiation; toxicities from ICI/targeted therapy in combination or in sequence; and potential strategies to enhance ICI efficacy in oncogene-driven non-small-cell lung cancers.

Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Is a Promising Signature to Predict Prognosis and Therapies for Hepatocellular Carcinoma (HCC)

BACKGROUND

The roles of mitochondria and the endoplasmic reticulum (ER) in the progression of hepatocellular carcinoma (HCC) are well established. However, a special domain that regulates the close contact between the ER and mitochondria, known as the mitochondria-associated endoplasmic reticulum membrane (MAM), has not yet been investigated in detail in HCC.

METHODS

The TCGA-LIHC dataset was only used as a training set. In addition, the ICGC and several GEO datasets were used for validation. Consensus clustering was applied to test the prognostic value of the MAM-associated genes. Then, the MAM score was constructed using the lasso algorithm. In addition, uncertainty of clustering in single-cell RNA-seq data using a gene co-expression network (AUCell) was used for the detection of the MAM scores in various cell types. Then, CellChat analysis was applied for comparing the interaction strength between the different MAM score groups. Further, the tumor microenvironment score (TME score) was calculated to compare the prognostic values, the correlation with the other HCC subtypes, tumor immune infiltration landscape, genomic mutations, and copy number variations (CNV) of different subgroups. Finally, the response to immune therapy and sensitivity to chemotherapy were also determined.

RESULTS

First, it was observed that the MAM-associated genes could differentiate the survival rates of HCC. Then, the MAM score was constructed and validated using the TCGA and ICGC datasets, respectively. The AUCell analysis indicated that the MAM score was higher in the malignant cells. In addition, enrichment analysis demonstrated that malignant cells with a high MAM score were positively correlated with energy metabolism pathways. Furthermore, the CellChat analysis indicated that the interaction strength was reinforced between the high-MAM-score malignant cells and T cells. Finally, the TME score was constructed, which demonstrated that the HCC patients with high MAM scores/low TME scores tend to have a worse prognosis and high frequency of genomic mutations, while those with low MAM scores/high TME scores were more likely to have a better response to immune therapy.

CONCLUSIONS

MAM score is a promising index for determining the need for chemotherapy, which reflects the energy metabolic pathways. A combination of the MAM score and TME score could be a better indicator to predict prognosis and response to immune therapy.

Efficacy and clinicogenomic correlates of response to immune checkpoint inhibitors alone or with chemotherapy in non-small cell lung cancer

The role of combination chemotherapy with immune checkpoint inhibitors (ICI) (ICI-chemo) over ICI monotherapy (ICI-mono) in non-small cell lung cancer (NSCLC) remains underexplored. In this retrospective study of 1133 NSCLC patients, treatment with ICI-mono vs ICI-chemo associate with higher rates of early progression, but similar long-term progression-free and overall survival. Sequential vs concurrent ICI and chemotherapy have similar long-term survival, suggesting no synergism from combination therapy. Integrative modeling identified PD-L1, disease burden (Stage IVb; liver metastases), and STK11 and JAK2 alterations as features associate with a higher likelihood of early progression on ICI-mono. CDKN2A alterations associate with worse long-term outcomes in ICI-chemo patients. These results are validated in independent external (n = 89) and internal (n = 393) cohorts. This real-world study suggests that ICI-chemo may protect against early progression but does not influence overall survival, and nominates features that identify those patients at risk for early progression who may maximally benefit from ICI-chemo.

Prognosis and personalized medicine prediction by integrated whole exome and transcriptome sequencing of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a clinically and genetically heterogeneous disease. To better describe the clinical value of the main driver gene mutations of HCC, we analyzed the whole exome sequencing data of 125 patients, and combined with the mutation data in the public database, 14 main mutant genes were identified. And we explored the correlation between the main mutation genes and clinical features. Consistent with the results of previous data, we found that TP53 and LRP1B mutations were related to the prognosis of our patients by WES data analysis. And we further explored the associated characteristics of TP53 and LRP1B mutations. However, it is of great clinical significance to tailor a unique prediction method and treatment plan for HCC patients according to the mutation of TP53. For TP53 wild-type HCC patients, we proposed a prognostic risk model based on 11 genes for better predictive value. According to the median risk score of the model, HCC patients with wild-type TP53 were divided into high-risk and low-risk groups. We found significant transcriptome changes in the enrichment of metabolic-related pathways and immunological characteristics between the two groups, suggesting the predictability of HCC immunotherapy by using this model. Through the CMap database, we found that AM580 had potential therapeutic significance for high-risk TP53 wild-type HCC patients.

Overall survival and role of programmed death ligand 1 expression in patients with metastatic non-small-cell lung cancer and immunotherapy: an observational study from central Switzerland

BACKGROUND

In clinical trials, therapy with immune checkpoint inhibitors has improved the survival of patients with metastatic non-small-cell lung cancer (NSCLC). These trials were important for drug approval and for defining new treatment standards but the effect of checkpoint inhibitors in patients treated outside of clinical trials is not well known. The goal of this study was to assess the effect of immunotherapy on the overall survival of patients with metastatic NSCLC in the region of central Switzerland.

MATERIALS AND METHODS

The study included 274 patients with histologically confirmed metastatic (stage IV) NSCLC in central Switzerland in the years 2015 to 2018. Patients with NSCLC and actionable driver mutations were excluded. Patients with checkpoint inhibitor treatment (immuno-oncology [IO] group, n = 122) were compared with patients without checkpoint inhibitor treatment (no-IO group, n = 152). Baseline demographics, disease characteristics and therapies applied were collected retrospectively. The primary endpoint was median overall survival calculated either from diagnosis or from the start of checkpoint inhibitor therapy to death or data cut-off (21 July 2021). We used the Kaplan-Meier method and an adjusted Cox proportional-hazards regression model. The expression of programmed-death ligand 1 (PD-L1) on tumour cells was used for exploratory analysis.

RESULTS

Patients had a median age of 68.4 years, most were male (61.7%) and more than half were current or former smokers (65%). A test for PD-L1 expression was available for 55.8% of the tumours. Patients in the IO group were younger than patients in the no-IO group. Among the 122 patients in the IO group, the median overall survival was 15 months (95% confidence interval [CI] 12-20). In the no-IO group, the median overall survival was 4 months (95% CI 3-7) with chemotherapy and 2 months (95% CI 1-2) with best supportive care. Patients with high (≥50%) PD-L1 expression and checkpoint inhibitor therapy had a slightly longer overall survival than patients with low PD-L1 and checkpoint inhibitor therapy.

CONCLUSION

These results suggest that treatment with checkpoint inhibitors improves overall survival in patients with metastatic NSCLC and that PD-L1 expression could have a predictive value in patients treated outside of clinical trials. Further studies are needed to study the magnitude of the benefit of checkpoint inhibitors according to molecular NSCLC subtype.

Associations of tissue tumor mutational burden and mutational status with clinical outcomes in KEYNOTE-042: pembrolizumab versus chemotherapy for advanced PD-L1-positive NSCLC

BACKGROUND

We evaluated whether tissue tumor mutational burden (tTMB) and STK11, KEAP1, and KRAS mutations have clinical utility as biomarkers for pembrolizumab monotherapy versus platinum-based chemotherapy in patients with programmed death ligand- 1 (PD-L1)-positive (tumor proportion score ≥1%) advanced/metastatic non-small-cell lung cancer (NSCLC) without EGFR/ALK alterations in the phase III KEYNOTE-042 trial.

PATIENTS AND METHODS

This retrospective exploratory analysis assessed prevalence of tTMB and STK11, KEAP1, and KRAS mutations determined by whole-exome sequencing of tumor tissue and matched normal DNA and their associations with outcomes in KEYNOTE-042. Clinical utility of tTMB was assessed using a prespecified cut point of 175 mutations/exome.

RESULTS

Of 793 patients, 345 (43.5%) had tTMB ≥175 mutations/exome and 448 patients (56.5%) had tTMB <175 mutations/exome. No association was observed between PD-L1 expression and tTMB. Continuous tTMB score was associated with improved overall survival (OS) and progression-free survival among patients receiving pembrolizumab (Wald test, one-sided P < 0.001) but not those receiving chemotherapy (Wald test, two-sided P > 0.05). tTMB ≥175 mutations/exome was associated with improved outcomes for pembrolizumab versus chemotherapy, whereas tTMB <175 mutations/exome was not {OS: hazard ratio, 0.62 [95% confidence interval (CI) 0.48-0.80] and 1.09 (95% CI 0.88-1.36); progression-free survival: 0.75 (0.59-0.95) and 1.27 (1.04-1.55), respectively}. Improved OS [hazard ratio (95% CI)] for pembrolizumab versus chemotherapy was observed regardless of STK11 [STK11 mutant (n = 33): 0.37 (0.16-0.86), STK11 wild-type (n = 396): 0.83 (0.65-1.05)]; KEAP1 [KEAP1 mutant (n = 64): 0.75 (0.42-1.35), KEAP1 wild-type (n = 365): 0.78 (0.61-0.99)], or KRAS [KRAS mutant (n = 69): 0.42 (0.22-0.81); KRAS wild-type (n = 232): 0.86 (0.63-1.18)] mutation status.

CONCLUSION

tTMB with a cut point of ≥175 mutations/exome is a potential predictive biomarker for pembrolizumab monotherapy for advanced/metastatic PD-L1 tumor proportion score ≥1% NSCLC. Pembrolizumab is a standard first-line treatment in this setting regardless of STK11, KEAP1, or KRAS mutation status.

Predictive value of p53 and AXL immunostaining for the efficacy of immune checkpoint inhibitor-based therapy after osimertinib treatment in patients with epidermal growth factor-mutant non-small cell lung cancer

BACKGROUND

Current evidence indicates that immune checkpoint inhibitors (ICIs) have a limited efficacy in patients with lung cancer harboring epidermal growth factor receptor (EGFR) mutations. However, there is a lack of data on the efficacy of ICIs after osimertinib treatment, and the predictors of ICI efficacy are unclear.

METHODS

We retrospectively assessed consecutive patients with EGFR-mutant NSCLC who received ICI-based therapy after osimertinib treatment at 10 institutions in Japan, between March 2016 and March 2021. Immunohistochemical staining was used to evaluate the expression of p53 and AXL. The deletions of exon 19 and the exon 21 L858R point mutation in EGFR were defined as common mutations; other mutations were defined as uncommon mutations.

RESULTS

A total of 36 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. In multivariate analysis, p53 expression in tumors was an independent predictor of PFS after ICI-based therapy (p = 0.002). In patients with common EGFR mutations, high AXL expression was a predictor of shorter PFS and overall survival after ICI-based therapy (log-rank test; p = 0.04 and p = 0.02, respectively).

CONCLUSION

The levels of p53 in pretreatment tumors may be a predictor of ICI-based therapy outcomes in patients with EGFR-mutant NSCLC after osimertinib treatment. High levels of AXL in tumors may also be a predictor of ICI-based therapy outcomes, specifically for patients with common EGFR mutations. Further prospective large-scale investigations on the predictors of ICI efficacy following osimertinib treatment are warranted.

Advances in artificial intelligence to predict cancer immunotherapy efficacy

Tumor immunotherapy, particularly the use of immune checkpoint inhibitors, has yielded impressive clinical benefits. Therefore, it is critical to accurately screen individuals for immunotherapy sensitivity and forecast its efficacy. With the application of artificial intelligence (AI) in the medical field in recent years, an increasing number of studies have indicated that the efficacy of immunotherapy can be better anticipated with the help of AI technology to reach precision medicine. This article focuses on the current prediction models based on information from histopathological slides, imaging-omics, genomics, and proteomics, and reviews their research progress and applications. Furthermore, we also discuss the existing challenges encountered by AI in the field of immunotherapy, as well as the future directions that need to be improved, to provide a point of reference for the early implementation of AI-assisted diagnosis and treatment systems in the future.

Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies

The high primary resistance incidence and unavoidable secondary resistance are the major clinical obstacle to lasting long-term benefits in Non-small-cell lung cancer (NSCLC) patients treated with immunotherapy. The mechanisms of immunotherapy resistance in NSCLC are complex, mainly involving tumor cells and tumor microenvironment (TME) infiltrating immune cells, including TAMs, B cells, NK cells, and T cells. The selection of clinical strategies for NSCLC progression after immunotherapy resistance should depend on the progressive mode. The progression pattern of NSCLC patients after immunotherapy resistance can be divided into oligo-progression and systemic/multiple progression, which should be considered for further treatment selection. In the future, it needs to explore how to optimize the combined therapy and explore strategies to reprogram infiltrating immune cells under various genetic backgrounds of tumor cells and timely reshape TME during antitumor treatments.

Targeting immune cell types of tumor microenvironment to overcome resistance to PD-1/PD-L1 blockade in lung cancer

Lung cancer is the common malignant tumor with the highest mortality rate. Lung cancer patients have achieved benefits from immunotherapy, including immune checkpoint inhibitors (ICIs) therapy. Unfortunately, cancer patients acquire adaptive immune resistance, leading to poor prognosis. Tumor microenvironment (TME) has been demonstrated to play a critical role in participating in acquired adaptive immune resistance. TME is associated with molecular heterogeneity of immunotherapy efficacy in lung cancer. In this article, we discuss how immune cell types of TME are correlated with immunotherapy in lung cancer. Moreover, we describe the efficacy of immunotherapy in driven gene mutations in lung cancer, including KRAS, TP53, EGFR, ALK, ROS1, KEAP1, ZFHX3, PTCH1, PAK7, UBE3A, TNF-α, NOTCH, LRP1B, FBXW7, and STK11. We also emphasize that modulation of immune cell types of TME could be a promising strategy for improving adaptive immune resistance in lung cancer.

TGF-β: A novel predictor and target for anti-PD-1/PD-L1 therapy

Transforming growth factor-β (TGF-β) signaling regulates multiple physiological processes, such as cell proliferation, differentiation, immune homeostasis, and wound healing. Besides, TGF-β plays a vital role in diseases, including cancer. Accumulating evidence indicates that TGF-β controls the composition and behavior of immune components in the tumor microenvironment (TME). Advanced cancers leverage TGF-β to reshape the TME and escape immune surveillance. TGF-β-mediated immune evasion is an unfavorable factor for cancer immunotherapy, especially immune checkpoint inhibitors (ICI). Numerous preclinical and clinical studies have demonstrated that hyperactive TGF-β signaling is closely associated with ICI resistance. It has been validated that TGF-β blockade synergizes with ICI and overcomes treatment resistance. TGF-β-targeted therapies, including trap and bispecific antibodies, have shown immense potential for cancer immunotherapy. In this review, we summarized the predictive value of TGF-β signaling and the prospects of TGF-β-targeted therapies for cancer immunotherapy.

High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is characterized by molecular heterogeneity with diverse immune cell infiltration patterns, which has been linked to therapy sensitivity and resistance. However, full understanding of how immune cell phenotypes vary across different patient subgroups is lacking. Here, we dissect the NSCLC tumor microenvironment at high resolution by integrating 1,283,972 single cells from 556 samples and 318 patients across 29 datasets, including our dataset capturing cells with low mRNA content. We stratify patients into immune-deserted, B cell, T cell, and myeloid cell subtypes. Using bulk samples with genomic and clinical information, we identify cellular components associated with tumor histology and genotypes. We then focus on the analysis of tissue-resident neutrophils (TRNs) and uncover distinct subpopulations that acquire new functional properties in the tissue microenvironment, providing evidence for the plasticity of TRNs. Finally, we show that a TRN-derived gene signature is associated with anti-programmed cell death ligand 1 (PD-L1) treatment failure.

Revealing the functions of clonal driver gene mutations in patients based on evolutionary dependencies

The clonal mutations in driver genes enable cells to gradually acquire growth advantage in tumor development. Therefore, revealing the functions of clonal driver gene mutations is important. Here, we proposed the method FCMP that considered evolutionary dependencies to analyze the functions of clonal driver gene mutations in a single patient. Applying our method to five cancer types from The Cancer Genome Atlas, we identified specific functions and common functions of clonal driver gene mutations. We found that the clonal driver gene mutations in the same patient played multiple functions. We also found that clonal mutations in the same driver gene performed different functions in different patients. These findings suggested that the clonal driver gene mutations showed strong tumor heterogeneity. In the pan-cancer analysis, the immune-related functions for clonal driver gene mutations were shared by multiple cancer types. In addition, clonal mutations in some driver genes predicted the survival of patients in cancers.

Non‑small cell lung cancer carrying PBRM1 mutation suggests an immunologically cold phenotype leading to immunotherapy failure even with high TMB

High tumor mutation load (TMB-H, or TMB ≥ 10) has been approved by the U.S. FDA as a biomarker for pembrolizumab treatment of solid tumors, including non‑small cell lung cancer (NSCLC). Patients with cancer who have immunotherapy-resistant gene mutations cannot achieve clinical benefits even in TMB-H. In this study, we aimed to identify gene mutations associated with immunotherapy resistance and further informed mechanisms in NSCLC. A combined cohort of 350 immune checkpoint blockade-treated patients from Memorial Sloan Kettering Cancer Center (MSKCC) was used to identify genes whose mutations could negatively influence immunotherapy efficacy. An external NSCLC cohort for which profession-free survival (PFS) data were available was used for independent validation. CIBERSORT algorithms were used to characterize tumor immune infiltrating patterns. Immunogenomic features were analysed in the TCGA NSCLC cohort. We observed that PBRM1 mutations independently and negatively influence immunotherapy efficacy. Survival analysis showed that the overall survival (OS) and PFS of patients with PBRM1 mutations (MT) were significantly shorter than the wild type (WT). Moreover, compared with PBRM1-WT/TMB-H group, OS was worse in the PBRM1-MT/TMB-H group. Notably, in patients with TMB-H/PBRM1-MT, it was equal to that in the low-TMB group. The CIBERSORT algorithm further confirmed that the immune infiltration abundance of CD8+ T cells and activated CD4+ memory T was significantly lower in the MT group. Immunogenomic differences were observed in terms of immune signatures, T-cell receptor repertoire, and immune-related genes between WT and MT groups. Nevertheless, we noticed an inverse relationship, given that MT tumors had a higher TMB than the WT group in MSKCC and TCGA cohort. In conclusion, our study revealed that NSCLC with PBRM1 mutation might be an immunologically cold phenotype and exhibited immunotherapy resistance. NSCLC with PBRM1 mutation might be misclassified as immunoresponsive based on TMB.

NKp44-Derived Peptide Used in Combination Stimulates Antineoplastic Efficacy of Targeted Therapeutic Drugs

Lung cancer cells in the tumor microenvironment facilitate immune evasion that leads to failure of conventional chemotherapies, despite provisionally decided on the genetic diagnosis of patients in a clinical setup. The current study follows three lung cancer patients who underwent "personalized" chemotherapeutic intervention. Patient-derived xenografts (PDXs) were subjected to tumor microarray and treatment screening with chemotherapies, either individually or in combination with the peptide R11-NLS-pep8; this peptide targets both membrane-associated and nuclear PCNA. Ex vivo, employing PDX-derived explants, it was found that combination with R11-NLS-pep8 stimulated antineoplastic effect of chemotherapies that were, although predicted based on the patient's genetic mutation, inactive on their own. Furthermore, treatment in vivo of PDX-bearing mice showed an exactly similar trend in the result, corroborating the finding to be translated into clinical setup.

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade

Different biomarkers based on genomics variants have been used to predict the response of patients treated with PD-1/programmed death receptor 1 ligand (PD-L1) blockade. We aimed to use deep-learning algorithm to estimate clinical benefit in patients with non-small-cell lung cancer (NSCLC) before immunotherapy. Peripheral blood samples or tumor tissues of 915 patients from three independent centers were profiled by whole-exome sequencing or next-generation sequencing. Based on convolutional neural network (CNN) and three conventional machine learning (cML) methods, we used multi-panels to train the models for predicting the durable clinical benefit (DCB) and combined them to develop a nomogram model for predicting prognosis. In the three cohorts, the CNN achieved the highest area under the curve of predicting DCB among cML, PD-L1 expression, and tumor mutational burden (area under the curve [AUC] = 0.965, 95% confidence interval [CI]: 0.949–0.978, P< 0.001; AUC =0.965, 95% CI: 0.940–0.989, P< 0.001; AUC = 0.959, 95% CI: 0.942–0.976, P< 0.001, respectively). Patients with CNN-high had longer progression-free survival (PFS) and overall survival (OS) than patients with CNN-low in the three cohorts. Subgroup analysis confirmed the efficient predictive ability of CNN. Combining three cML methods (CNN, SVM, and RF) yielded a robust comprehensive nomogram for predicting PFS and OS in the three cohorts (each P< 0.001). The proposed deep-learning method based on mutational genes revealed the potential value of clinical benefit prediction in patients with NSCLC and provides novel insights for combined machine learning in PD-1/PD-L1 blockade.

KRAS in NSCLC: State of the Art and Future Perspectives

In NSCLC, KRAS mutations occur in up to 30% of all cases, most frequently at codon 12 and 13. KRAS mutations have been linked to adenocarcinoma histology, positive smoking history, and Caucasian ethnicity, although differences have been described across KRAS mutational variants subtypes. KRAS mutations often concur with other molecular alterations, notably TP53, STK11, and KEAP1, which could play an important role in treatment efficacy and patient outcomes. For many years, KRAS mutations have been considered undruggable mainly due to a high toxicity profile and low specificity of compounds. Sotorasib and adagrasib are novel KRAS inhibitors that recently gained FDA approval for pre-treated KRAS mutant NSCLC patients, and other molecules such as GDC-6036 are currently being investigated with promising results. Despite their approval, the efficacy of these drugs is lower than expected and progression among responders has been reported. Mechanisms of acquired resistance to anti-KRAS molecules typically involves either on target secondary mutations (e.g., G12, G13, Q61H, R68S, H95, Y96C, V8L) or off-target alterations. Ongoing trials are currently evaluating strategies for implementing efficacy and overcoming acquired resistance to these compounds. Finally, the efficacy of immune-checkpoint inhibitors still needs to be completely assessed and responses to anti-PD-1/PD-L1 agents may strongly depend on concomitant mutations.

Netie: inferring the evolution of neoantigen-T cell interactions in tumors

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8⁺ T cell interactions in tumors. Netie was systematically validated and applied to examine the molecular patterns of 3,219 tumors, compiled from a panel of 18 cancer types. We showed that tumors with an increase in immune selection pressure over time are associated with T cells that have an activation-related expression signature. We also identified a subset of exhausted cytotoxic T cells postimmunotherapy associated with tumor clones that newly arise after treatment. These analyses demonstrate how netie enables the interrogation of the relationship between individual neoantigen repertoires and the tumor molecular profiles. We found that a T cell inflammation gene expression profile (TIGEP) is more predictive of patient outcomes in the tumors with an increase in immune pressure over time, which reveals a curious synergy between T cells and neoantigen distributions. Overall, we provide a new tool that is capable of revealing the imprints left by neoantigens during each tumor's developmental process and of predicting how tumors will progress under further pressure of the host's immune system.

Clinical and Molecular Features of KRAS-Mutated Lung Cancer Patients Treated with Immune Checkpoint Inhibitors

Background: The molecular and clinical features of KRAS-mutated lung cancer patients treated with immunotherapy have yet to be characterized, which could guide the development of therapeutics targeting KRAS with potential immuno-oncology treatment combinations. Research Question: Do KRAS-mutated patients with different subtypes and comutations have different clinical responses and overall survival (OS) to checkpoint inhibitors? Study Design and Methods: 87 patients with NSCLC at the City of Hope who received immune checkpoint inhibitors were identified and analyzed retrospectively. Tumor genomic alterations were extracted from the clinical data with next-generation sequencing using various platforms. Demographic, clinical, molecular, and pathological information was collected with the approval of the institutional review board of the City of Hope. OS was calculated if it was available at the study time point, and responses were determined according to the RECIST v1.1. Results: Among 87 patients, 32 had a KRAS G12C mutation (36.8%), 19 had G12V (21.9%), 18 had G12D (20.7%), 6 had G12A (6.9%), 3 had G12R (3.45%), and 10 had amplification (11.49%) and other uncommon mutations. G12D had a statistically significant Odds Ratio (OR) between patients who had responses and progression of the disease (OR (95% CI) = 0.31 (0.09−0.95), p < 0.05), with 5 G12D-mutated patients having responses and 11 G12D-mutated patients having progression of the disease. In the univariate analysis with OS, there was a trend of better OS in the G12D-mutated patients, with no statistically significant difference in terms of OS between the patients who had G12D mutation and the patients who had other KRAS mutations (HR (95% CI) = 0.53 (0.21−1.36), p = 0.185). The median OS was significantly worse with KRAS comutation CDKN2A/B loss (4.2 vs. 16.9 months, HR = 3.07 (1.09−8.69), p < 0.05) and MET (3.4 vs. 17 months, HR = 3.80 (1.44−10.05), p < 0.01), which were included for the multivariate analysis. The OS with other KRAS comutations was not statistically significant, including STK11 and KEAP1. Conclusion: KRAS mutation subtypes such as G12D and comutations such as CDKN2/A and MET may modulate the immunotherapy responses and outcomes in lung cancer.

Genomic landscape of lung adenocarcinomas in different races

Background

Lung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood.

Methods

We analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes.

Results

Native Americans had significantly higher rates of insertions and deletions than other races (P<0.001). Among patients with lung adenocarcinomas, EGFR and KRAS were the highest discrepancy genes in the different racial groups (P<0.001). The EGFR exon 21 L858R point mutation was three times higher in Asians than in all other races (P<0.001). Asians, Whites, and Blacks had 4.7%, 3.1%, and 1.8% ALK rearrangement, respectively (P<0.001). White patients had the highest rates of reported KRAS G12C (15.51%) than other races (P<0.001). Whites (17.2%), Blacks (15.1%), and Other (15.7%) had higher rates of STK11 mutation than Asians (3.94%) (P<0.001). RET rearrangement and ERBB2 amplification were more common in Asian patients than in Other racial groups. Apart from point mutations, structural variations, and fusion genes, we identified a significant amount of copy number alterations in each race.

Conclusions

The tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.

Non-small-cell lung cancer patients harboring TP53/KRAS co-mutation could benefit from a PD-L1 inhibitor

Aim: To explore the association between TP53 mutation and atezolizumab in non-small-cell lung cancer (NSCLC) patients. Materials & methods: Patients with NSCLC from the POPLAR and OAK studies were included. Kaplan-Meier analysis was performed to detect progression-free survival (PFS) and overall survival (OS). PFS and OS were compared using multivariate Cox regression analysis. Results: OS was significantly longer with atezolizumab compared with docetaxel among TP53/KRAS co-mutant NSCLC patients (hazard ratio [HR]: 0.014; 95% CI: 0.000-0.721). There is no significant OS difference between atezolizumab versus docetaxel for TP53-mutant NSCLC patients (HR: 0.831; 95% CI: 0.473-1.458). There is no significant OS difference between atezolizumab versus docetaxel for KRAS-mutant NSCLC patients (HR: 1.354; 95% CI: 0.528-3.472). Conclusion: PD-L1 inhibitors may bring OS benefits for patients with NSCLC harbored TP53/KRAS co-mutation.

Neoadjuvant Immunotherapy Combined with Chemotherapy for Local Advanced Non-Small-Cell Lung Cancer in a Patient with a History of Breast Cancer: A Case Report

Durvalumab consolidation therapy is the standard treatment after concurrent chemoradiotherapy for patients with surgically unresectable stage IIIA (N2) non-small-cell lung cancer (NSCLC). Neoadjuvant therapy followed by surgery could reduce locoregional and distant recurrence and improve the survival rate for surgically resectable NSCLC. However, the value of neoadjuvant therapy in locally advanced potentially resectable NSCLC remains controversial. Herein, we report a locally advanced potentially resectable NSCLC case with a history of breast cancer who achieved a pathologic complete response (pCR) after preoperative treatment with pembrolizumab and chemotherapy. A 50-year-old woman developed squamous cell carcinoma (SCC) (left lower lobe of the lung, stage IIIA-N2) after two years of chemotherapy and anti-HER2 therapy following a diagnosis of HER2-overexpressing breast cancer. Surgical resection was attempted despite an MDT classification as unamenable to curative surgical resection. After two cycles of neoadjuvant chemotherapy combined with anti-PD1 immunotherapy, the tumor significantly shrank, then the patient underwent a left lower lobectomy. Complete resection with negative margins (R0 resection) was achieved in the patient. The patient experienced grade 1–2 adverse effects and no grade 3 or worse adverse effects occurred. Cardiotoxicity did not occur in the patient despite prior anti-HER2 treatment for breast cancer. Our case study contributes to the existing evidence on the feasibility, efficacy, and safety of neoadjuvant immunotherapy combined with chemotherapy in locally advanced unresectable NSCLC. Furthermore, future studies are needed to determine which patients can benefit from immunoadjuvant therapy and the duration and course of preoperative and postoperative immunotherapy.

Prognostic role of multiple abnormal genes in non-small-cell lung cancer

BACKGROUND

Non-small-cell lung cancer (NSCLC) has the highest morbidity and mortality rates among all malignant tumor types. Although therapies targeting the mutated genes such as KRAS have been used in the clinic for many years, the prognosis remains poor. Therefore, it is necessary to further study the aberrant expression or mutation of non-target genes affecting the survival and prognosis.

AIM

To explore the impact of simultaneous abnormalities of multiple genes on the prognosis and survival of patients.

METHODS

We used R packages to analyze gene expression data and clinical data downloaded from The Cancer Genome Atlas (TCGA) database. We also collected samples from 85 NSCLC patients from the First People's Hospital of Jingzhou City and retrospectively followed the patients. Multivariate Cox regression analysis and survival analysis were performed.

RESULTS

Analysis of gene expression data from TCGA revealed that the overexpression of the following single genes affected overall survival: TP53 (P = 0.79), PTEN (P = 0.94), RB1 (P = 0.49), CTNNB1 (P = 0.24), STK11 (P = 0.32), and PIK3CA (P = 0.013). However, the probability of multiple genes (TP53, PTEN, RB1, and STK11) affecting survival was 0.025. Retrospective analysis of clinical data revealed that sex (hazard ratio [HR] = 1.29; [95%CI: 0.64-2.62]), age (HR = 1.05; [95%CI: 1.02-1.07]), smoking status (HR = 2.26; [95%CI: 1.16-4.39]), tumor histology (HR = 0.58; [95%CI: 0.30-1.11]), cancer stage (HR = 16.63; [95%CI: 4.8-57.63]), epidermal growth factor receptor (EGFR) mutation (HR = 1.82; [95%CI: 1.05-3.16]), abundance (HR = 4.95; [95%CI: 0.78-31.36]), and treatment with tyrosine kinase inhibitors (TKIs) (HR = 0.58; [95%CI: 0.43-0.78]) affected patient survival. Co-occurring mutations of TP53, PTEN, RB1, and STK11 did not significantly affect the overall survival of patients receiving chemotherapy (P = 0.96) but significantly affected the overall survival of patients receiving TKIs (P = 0.045).

CONCLUSION

Co-occurring mutation or overexpression of different genes has different effects on the overall survival and prognosis of NSCLC patients. Combined with TKI treatment, the co-occurring mutation of some genes may have a synergistic effect on the survival and prognosis of NSCLC patients.

NOTCH1 mutation associates with impaired immune response and decreased relapse-free survival in patients with resected T1-2N0 laryngeal cancer

Background

Patients with early-stage laryngeal cancer, even stage T1-2N0, are at considerable risk of recurrence and death. The genetic and immunologic characteristics of recurrent laryngeal cancer remain unclear.

Methods

A total of 52 T1-2N0 laryngeal cancer patients were enrolled. Of these, 42 tissue samples were performed by targeted DNA sequencing, and 21 cases were performed by NanoString immuno-oncology targeted RNA sequencing to identify the distinct molecular bases and immunologic features associated with relapse in patients with early laryngeal cancer, respectively.

Results

To the best to our knowledge, we present for the first time an overview of the genomic mutation spectrum of early-stage laryngeal cancers. A total of 469 genomic alterations were detected in 211 distinct cancer-relevant genes, and the genes found to be mutated in more than five patients (>10%) included tumor protein p53 (TP53, 78.5%), FAT atypical cadherin 1 (FAT1, 26%), LDL receptor related protein 1B (LRP1B, 19%), cyclin dependent kinase inhibitor 2A (CDKN2A, 17%), tet methylcytosine dioxygenase 2 (TET2, 17%), notch receptor 1 (NOTCH1, 12%) and neuregulin 1 (NRG1, 12%). Recurrent laryngeal cancer demonstrated a higher tumor mutation burden (TMB), as well as higher LRP1B mutation and NOTCH1 mutation rates. Univariate and multivariate analyses revealed that high TMB (TMB-H) and NOTCH1 mutation are independent genetic factors that are significantly associated with shorter relapse-free survival (RFS). Simultaneously, the results of the transcriptome analysis presented recurrent tumors with NOTCH1 mutation displayed upregulation of the cell cycle pathway, along with decreased B cells score, T cells score, immune signature score and tumor-infiltrating lymphocytes (TILs) score. The Cancer Genome Atlas (TCGA)-laryngeal cancer dataset also revealed weakened immune response and impaired adhesion functions in NOTCH1-mutant patients.

Conclusions

Genomic instability and impaired immune response are key features of the immunosurveillance escape and recurrence of early laryngeal cancer after surgery. These findings revealed immunophenotypic attenuation in recurrent tumors and provided valuable information for improving the management of these high-risk patients. Due to the small number of patients in this study, these differences need to be further validated in a larger cohort.

Necroptosis Identifies Novel Molecular Phenotypes and Influences Tumor Immune Microenvironment of Lung Adenocarcinoma

This study aims to investigate the immune and epigenetic mutational landscape of necroptosis in lung adenocarcinoma (LUAD), identify novel molecular phenotypes, and develop a prognostic scoring system based on necroptosis regulatory molecules for a better understanding of the tumor immune microenvironment (TIME) in LUAD. Based on the Cancer Genome Atlas and Gene Expression Omnibus database, a total of 29 overlapped necroptosis-related genes were enrolled to classify patients into different necroptosis phenotypes using unsupervised consensus clustering. We systematically correlated the phenotypes with clinical features, immunocyte infiltrating levels, and epigenetic mutation characteristics. A novel scoring system was then constructed, termed NecroScore, to quantify necroptosis of LUAD by principal component analysis. Three distinct necroptosis phenotypes were confirmed. Two clusters with high expression of necroptosis-related regulators were “hot tumors”, while another phenotype with low expression was a “cold tumor”. Molecular characteristics, including mutational frequency and types, copy number variation, and regulon activity differed significantly among the subtypes. The NecroScore, as an independent prognostic factor (HR=1.086, 95%CI=1.040-1.133, p<0.001), was able to predict the survival outcomes and show that patients with higher scores experienced a poorer prognosis. It could also evaluate the responses to immunotherapy and chemotherapeutic efficiency.

In conclusion, necroptosis-related molecules are correlated with genome diversity in pan-cancer, playing a significant role in forming the TIME of LUAD. Necroptosis phenotypes can distinguish different TIME and molecular features, and the NecroScore is a promising biomarker for predicting prognosis, as well as immuno- and chemotherapeutic benefits in LUAD.

CD8+ T-cell responses are boosted by dual PD-1/VEGFR2 blockade after EGFR inhibition in Egfr-mutant lung cancer

Epidermal growth factor receptor (EGFR) is the most frequently mutated driver oncogene in non-smoking-related, non-small-cell lung cancer (NSCLC). EGFR-mutant NSCLC has a non-inflamed tumor microenvironment (TME), with low infiltration by CD8+ T cells and, thus, immune checkpoint inhibitors, such as anti-programmed cell death-1 (anti-PD-1) have weak anti-tumor effects. Here, we showed that CD8+ T-cell responses were induced by an EGFR-tyrosine kinase inhibitor (TKI) in syngeneic Egfr-mutant NSCLC tumors, which was further pronounced by sequential dual blockade of PD-1 and vascular endothelial growth factor receptor 2 (VEGFR2). However, simultaneous triple blockade had no such effect. PD-1/VEGFR2 dual blockade did not exert tumor-inhibitory effects without pre-treatment with the EGFR-TKI, suggesting that treatment schedule is crucial for efficacy of the dual blockade therapy. Pre-treatment with EGFR-TKI increased the CD8+ T-cell/regulatory T-cell (Treg) ratio, while also increasing expression of immunosuppressive chemokines and chemokine receptors, as well as increasing the number of M2-like macrophages, in the TME. Discontinuing EGFR-TKI treatment reversed the transient increase of immunosuppressive factors in the TME. The subsequent PD-1/VEGFR2 inhibition maintained increased numbers of infiltrating CD8+ T cells and CD11c+ dendritic cells. Depletion of CD8+ T cells in vivo abolished tumor growth inhibition by EGFR-TKI alone and the sequential triple therapy, suggesting that EGFR inhibition is a prerequisite for the induction of CD8+ T-cell responses. Our findings could aid in developing an alternative immunotherapy strategy in patients with cancers that have driver mutations and a non-inflamed TME.

Association of thyroid transcription factor-1 with the efficacy of immune-checkpoint inhibitors in patients with advanced lung adenocarcinoma

Background

We aimed to identify the relationship between thyroid transcription factor‐1 (TTF‐1) expression of lung adenocarcinoma and the efficacy of immune‐checkpoint inhibitor (ICI) therapy.

Methods

This retrospective multicenter study comprised patients with advanced lung adenocarcinoma treated with ICI monotherapy. We collected clinical medical records including data on TTF‐1 expression and analyzed the relationship between TTF‐1 expression and programmed death‐ligand 1 tumor proportion score (PD‐L1 TPS), objective response rate (ORR), progression‐free survival (PFS), and overall survival (OS).

Results

In total, 108 patients with lung adenocarcinoma were analyzed. The rate of TPS ≥1% and ≥50% in patients with positive TTF‐1 expression was significantly higher than that in patients with negative TTF‐1 expression (88% vs. 60%, p < 0.001; 65% vs. 24%, p < 0.001). The ORR was significantly higher in TTF‐1 positive patients than in TTF‐1‐negative patients (38% vs. 8%, p = 0.003). Among patients with TPS ≥50% and 1%–49%, the ORR in TTF‐1 positive and negative patients was 48% (26/54) versus 17% (1/6) (p = 0.21), and 32% (6/19) versus 11% (1/9) (p = 0.37), respectively. The ORR for patients with TPS <1% was 0% in both the TTF‐1 negative and positive cases. The median PFS and OS was significantly longer in TTF‐1‐positive patients than in TTF‐1‐negative patients (5.4 vs. 1.6 months, p < 0.001; 18.2 vs. 8.0 months, p = 0.041). Multivariate analysis revealed that TTF‐1‐negative status was an independent unfavorable prognostic factor for PFS.

Conclusion

Patients with TTF‐1‐positive status receiving ICI monotherapy showed better outcomes than those with TTF‐1‐negative lung adenocarcinoma.