The Role of Tumor-Infiltrating Lymphocytes in Development, Progression, and Prognosis of Non-Small Cell Lung Cancer

Lymphocyte-to-C-reactive protein ratio predicts prognosis in unresectable locally advanced non-small cell lung cancer patients

BACKGROUND

The lymphocyte-to-C-reactive protein ratio (LCR) is a promising inflammation-based tool for assessing the status of patients with malignant tumours. This study evaluated the ability of LCR to predict the prognosis of patients with unresectable locally advanced non-small cell lung cancer (LA-NSCLC) after chemoradiotherapy.

METHODS

We retrospectively investigated 206 consecutive patients with unresectable LA-NSCLC who underwent chemoradiotherapy between January 2016 and November 2019. The LCR was calculated from the differential count by dividing the absolute lymphocyte count by the C-reactive protein level. The optimal cut-off value of LCR was determined using the receiver operating characteristic (ROC) curve, and the enrolled patients were divided into two groups for further analysis according to LCR. Overall survival (OS) and disease-free survival (DFS) were assessed using univariate and multivariate Cox regression analyses.

RESULTS

In patients with unresectable LA-NSCLC, the level of LCR was significantly associated with pathology (p = 0.042) and TNM stage (p = 0.002). High LCR and low LCR patients had different distinct outcomes (median OS: 36 vs. 34 months, p < 0.0001) and recurrence risk (median DFS: 31 vs. 23 months, p < 0.001). Univariate analysis indicated that Eastern Cooperative Oncology Group (ECOG) performance status, TNM stage, CEA level, response, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and LCR were predictors of OS and DFS. Multivariate analysis showed that a high LCR was an independent prognostic factor for OS (hazard ratio [HR], 0.526; 95% CI, 0.364-0.762; p = 0.001) and DFS (HR, 0.390; 95% CI, 0.275-0.554; p < 0.001).

CONCLUSION

LCR is a promising prognostic index in patients with LA-NSCLC undergoing chemoradiotherapy, and an increase in the LCR level contributes to better outcomes.

Direct cell interactions potentially regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy

The tumour microenvironment is composed of a complex cellular network involving cancer, stromal and immune cells in dynamic interactions. A large proportion of this network relies on direct physical interactions between cells, which may impact patient responses to clinical therapy. Doublets in scRNA-seq are usually excluded from analysis. However, they may represent directly interacting cells. To decipher the physical interaction landscape in relation to clinical prognosis, we inferred a physical cell-cell interaction (PCI) network from 'biological' doublets in a scRNA-seq dataset of approximately 18,000 cells, obtained from 7 treatment-naive ovarian cancer patients. Focusing on cancer-stromal PCIs, we uncovered molecular interaction networks and transcriptional landscapes that stratified patients in respect to their clinical responses to standard therapy. Good responders featured PCIs involving immune cells interacting with other cell types including cancer cells. Poor responders lacked immune cell interactions, but showed a high enrichment of cancer-stromal PCIs. To explore the molecular differences between cancer-stromal PCIs between responders and non-responders, we identified correlating gene signatures. We constructed ligand-receptor interaction networks and identified associated downstream pathways. The reconstruction of gene regulatory networks and trajectory analysis revealed distinct transcription factor (TF) clusters and gene modules that separated doublet cells by clinical outcomes. Our results indicate (i) that transcriptional changes resulting from PCIs predict the response of ovarian cancer patients to standard therapy, (ii) that immune reactivity of the host against the tumour enhances the efficacy of therapy, and (iii) that cancer-stromal cell interaction can have a dual effect either supporting or inhibiting therapy responses.

Thyroid hormone receptor interacting protein 13 is associated with prognosis and immunotherapy efficacy in human cancers: a pan-cancer analysis

Thyroid hormone receptor-interacting protein 13 (TRIP13) is involved in the regulation of mitosis and is overexpressed in multiple cancers. However, there is no systematic assessment of the role of TRIP13 in the immunotherapy response across human cancers. Therefore, a pan-cancer analysis involving expression, prognosis, immune-related mechanisms, and biomarker values was performed to explore the associations between TRIP13 expression and the immunotherapy response. TRIP13 is highly expressed in various types of cancer, increasing patient outcomes in eight types of cancer. TRIP13 expression was correlated with significant tumor mutation burden and microsatellite instability, and its mutations were linked with poor prognosis in patients with adrenocortical carcinoma. TRIP13 promoted endothelial cell and hematopoietic stem cell infiltration in human cancers. Additionally, TRIP13 mutation significantly increased the infiltration of CD8 + T cells in kidney renal clear cell carcinoma, which might contribute to poor prognosis. Furthermore, three key genes that interact with TRIP13 were identified: CDC20, RAD1, and MAD2L1, which are related to the cell cycle and ultimately promote tumorigenesis and proliferation. The expression of TRIP13 was significantly greater in kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and pancreatic adenocarcinoma cells than in corresponding normal cells according to qPCR. Taken together, these findings indicate that TRIP13 is associated with poor prognosis in eight human cancers and serves as a novel biomarker for predicting immunotherapy efficacy. Our first pan-cancer study contributes to personalized precision medicine in cancer immunotherapy, promoting subsequent clinical management and improving patient prognosis.

Metagenomics and Non-Targeted Metabolomics Reveal the Role of Gut Microbiota and Its Metabolites in Brain Metastasis of Non-Small Cell Lung Cancer

BACKGROUND

Brain metastasis is a common and severe complication in non-small cell lung cancer (NSCLC) patients, significantly affecting prognosis. However, the role of gut microbiota and its metabolites in NSCLC brain metastasis remains poorly understood. This study aims to explore the relationship between gut microbiota, metabolites, and the development of brain metastasis in NSCLC.

METHODS

We conducted an integrative analysis combining metagenomics and non-targeted metabolomics on baseline fecal samples from NSCLC patients with brain metastasis (n = 18) and those without distant metastasis (n = 12). Gut microbiota composition and metabolite profiles were detected and analyzed, and statistical methods, including machine learning models, were applied to identify differences and potential biomarkers.

RESULTS

Significant differences in gut microbiota composition were found between the two groups, with higher microbial diversity observed in patients with brain metastasis. Specific genera, such as Paenibacillus, Fournierella, and Adlercreutzia, were enriched in the brain metastasis group. Metabolomic analysis revealed altered levels of short-chain fatty acids and other metabolites associated with immune modulation and vascular permeability, including angiotensin (1-7). These changes were linked to the metastatic process and may influence brain metastasis development. Furthermore, machine learning models identified key biomarkers, such as Raoultibacter, Mobilibacterium, and N-acetyl-L-glutamic acid, which could serve as valuable indicators for brain metastasis.

CONCLUSIONS

Our findings suggest that gut microbiota dysbiosis and its metabolic products may contribute to the development of brain metastasis in NSCLC. The identification of microbiota-derived biomarkers holds potential for early detection and therapeutic intervention in NSCLC brain metastasis.

THSD7A as a novel prognostic factor for colorectal carcinoma

BACKGROUND

Thrombospondin type 1 domain-containing 7 A (THSD7A) expression, an angiogenesis-related protein, has been implicated in various aspects of cancer progression, reflecting its potential as a prognostic marker for various cancers. Therefore, we investigated the prognostic value of THSD7A expression in colorectal cancer (CRC).

METHODS

A total of 95 patients with CRC were included. The patients were stratified into two groups according to THSD7A expression status determined by immunohistochemistry [negative (no staining), and positive (expression ≥ 1% of cancer cells)]. The overall survival (OS) of prognostic subgroups was estimated by Kaplan Meier method. The prognostic value of THSD7A expression was evaluated by univariable and multivariable Cox regression models.

RESULTS

THSD7A was expressed in 42.1% of CRC patients. Patients with no THSD7A expression had inferior OS than patients with THSD7A expression (72.9 months vs. median OS was not reached, p = 0.001, respectively). Our multivariate analyses revealed that the independent predictors of OS were poor differentiation of tumor (HR: 2.603, p = 0.002), advanced stage (HR: 3.210, p < 0.001), and the loss of THSD7A expression (HR: 3.094, p = 0.001).

CONCLUSIONS

The present study showed that THSD7A expression could serve as a potential prognostic marker for CRC cancer. Further research is warranted to elucidate the exact underlying THSD7A-mediated cancer progression and to explore its clinical use in improving CRC prognostication and treatment strategies.

Prognostic and predictive values of a multimodal nomogram incorporating tumor and peritumor morphology with immune status in resectable lung adenocarcinoma

BACKGROUND

Current prognostic and predictive biomarkers for lung adenocarcinoma (LUAD) predominantly rely on unimodal approaches, limiting their characterization ability. There is an urgent need for a comprehensive and accurate biomarker to guide individualized adjuvant therapy decisions.

METHODS

In this retrospective study, data from patients with resectable LUAD (stage I-III) were collected from two hospitals and a publicly available dataset, forming a training dataset (n=223), a validation dataset (n=95), a testing dataset (n=449), and the non-small cell lung cancer (NSCLC) Radiogenomics dataset (n=59). Tumor and peritumor scores were constructed from preoperative CT radiomics features (shape/intensity/texture). An immune score was derived from the density of tumor-infiltrating lymphocytes (TILs) within the cancer epithelium and stroma on hematoxylin and eosin-stained whole-slide images. A clinical score was constructed based on clinicopathological risk factors. A Cox regression model was employed to integrate these scores, thereby constructing a multimodal nomogram to predict disease-free survival (DFS). The adjuvant chemotherapy benefit rate was subsequently calculated based on this nomogram.

RESULTS

The multimodal nomogram outperformed each of the unimodal scores in predicting DFS, with a C-index of 0.769 (vs 0.634-0.731) in the training dataset, 0.730 (vs 0.548-0.713) in the validation dataset, and 0.751 (vs 0.660-0.692) in the testing dataset. It was independently associated with DFS after adjusting for other clinicopathological risk factors (training dataset: HR=3.02, p<0.001; validation dataset: HR=2.33, p<0.001; testing dataset: HR=2.03, p=0.001). The adjuvant chemotherapy benefit rate effectively distinguished between patients benefiting from adjuvant chemotherapy and those from observation alone (interaction p<0.001). Furthermore, the high-/low-risk groups defined by the multimodal nomogram provided refined stratification of candidates for adjuvant chemotherapy identified by current guidelines (p<0.001). Gene set enrichment analyses using the NSCLC Radiogenomics dataset revealed associations between tumor/peritumor scores and pathways involved in epithelial-mesenchymal transition, angiogenesis, IL6-JAK-STAT3 signaling, and reactive oxidative species.

CONCLUSION

The multimodal nomogram, which incorporates tumor and peritumor morphology with anti-tumor immune response, provides superior prognostic accuracy compared with unimodal scores. Its defined adjuvant chemotherapy benefit rates can inform individualized adjuvant therapy decisions.

Spatial distribution of tertiary lymphoid structures in the molecular and clinical context of non-small cell lung cancer

INTRODUCTION

Tertiary lymphoid structures (TLS) are lymphocyte aggregates resembling secondary lymphoid organs and are pivotal in cancer immunity. The ambiguous morphological definition of TLS makes it challenging to ascertain their clinical impact on patient survival and response to immunotherapy.

OBJECTIVES

This study aimed to characterize TLS in hematoxylin-eosin tissue sections from lung cancer patients, assessing their occurrence in relation to the local immune environment, mutational background, and patient outcome.

METHODS

Two pathologists evaluated one whole tissue section from resection specimens of 680 NSCLC patients. TLS were spatially quantified within the tumor area or periphery and further categorized based on the presence of germinal centers (mature TLS). Metrics were integrated with immune cell counts, genomic and transcriptomic data, and correlated with clinical parameters.

RESULTS

TLS were present in 86% of 536 evaluable cases, predominantly in the tumor periphery, with a median of eight TLS per case. Mature TLS were found in 24% of cases. TLS presence correlated positively with increased plasma cell (CD138+) and lymphocytic cell (CD3+, CD8+, FOXP3+) infiltration. Tumors with higher tumor mutational burden exhibited higher numbers of peripheral TLS. The overall TLS quantity was independently associated with improved patient survival, irrespective of TLS maturation status. This prognostic association held true for peripheral TLS but not for tumor TLS.

CONCLUSION

TLS in NSCLC is common and their correlation with a specific immune phenotype suggests biological relevance in the local immune reaction. The prognostic significance of this scoring system on routine hematoxylin-eosin sections has the potential to augment diagnostic algorithms for NSCLC patients.

Molecular mechanisms of transcription factor KLF4-mediated immune infiltration influencing lung adenocarcinoma invasion

BACKGROUND

Lung adenocarcinoma (LUAD) is associated with an increasing incidence and mortality rate while existing treatment strategies continue to exhibit considerable limitation. Studies have demonstrated that upregulation of KLF4 gene inhibits LUAD progression, but its underlying mechanisms remain elusive. The present research explored roles and mechanisms of KLF4 and the NF-κB pathway in LUAD.

METHODS

Lentiviral vectors encoding KLF4 were constructed and transduced into H1299 and A549 cells to generate stable cell lines. These stable cell lines were then injected into BALB/c mice to establish a LUAD model. Subsequently, RNA sequencing, HE staining, immunohistochemistry, ELISA, Western blotting, and flow cytometry were employed to investigate the effects of KLF4 on tumor growth, invasion, immune cell infiltration, and related signaling pathways. Finally, dual-luciferase and in vivo mouse experiments were conducted to validate the molecular mechanisms.

RESULTS

KLF4 significantly reduced tumor cell invasion while promoted tumor cell necrosis. Transcriptomic sequencing identified CXCR2 as a target gene and the NF-κB signaling pathway associated with immune infiltration regulation. KLF4 downregulated NF-κB2 and CXCR2 expression, concomitantly decreasing tumor cell invasiveness but increasing levels of CD4+ and CD8+ T cells and macrophages.

CONCLUSION

NF-κB and CXCR2 play an important role in KLF4-mediated immune infiltration, thereby inhibiting tumor invasion and promoting tumor cell apoptosis in mice.

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to the treatment of lung squamous cell carcinoma (LUSC). However, there is a lack of optimal predictive models that can accurately forecast patient prognosis and guide the selection of targeted therapies. The extensive multi-omic data obtained from multi-level molecular biology provides a unique perspective for understanding the underlying biological characteristics of cancer, offering potential prognostic indicators and drug sensitivity biomarkers for LUSC patients. We integrated diverse datasets encompassing gene expression, DNA methylation, genomic mutations, and clinical data from LUSC patients to achieve consensus clustering using a suite of 10 multi-omics integration algorithms. Subsequently, we employed 10 commonly used machine learning algorithms, combining them into 101 unique configurations to design an optimal performing model. We then explored the characteristics of high- and low-risk LUSC patient groups in terms of the tumor microenvironment and response to immunotherapy, ultimately validating the functional roles of the model genes through in vitro experiments. Through the application of 10 clustering algorithms, we identified two prognostically relevant subtypes, with CS1 exhibiting a more favorable prognosis. We then constructed a subtype-specific machine learning model, LUSC multi-omics signature (LMS) based on seven key hub genes. Compared to previously published LUSC biomarkers, our LMS score demonstrated superior predictive performance. Patients with lower LMS scores had higher overall survival rates and better responses to immunotherapy. Notably, the high LMS group was more inclined toward "cold" tumors, characterized by immune suppression and exclusion, but drugs like dasatinib may represent promising therapeutic options for these patients. Notably, we also validated the model gene SERPINB13 through cell experiments, confirming its role as a potential oncogene influencing the progression of LUSC and as a promising therapeutic target. Our research provides new insights into refining the molecular classification of LUSC and further optimizing immunotherapy strategies.

Pan-cancer landscape analysis of NOP58 and its oncogenic driving role in lung adenocarcinoma

Despite improvements in treatment in recent years, patients with lung adenocarcinoma (LUAD) still face poor prognoses. In this study, we elucidated the potential role of NOP58 ribonucleoprotein in pan-cancer and validated its oncogenic significance in LUAD using bioinformatics and in vitro and in vivo functional assays. NOP58 was found to be overexpressed in various types of tumors. It had great precision for predicting 20 distinct cancer types using receiver operating characteristic curve (ROC) as well as significant connections with the prognoses in particular cancers. In LUAD, NOP58 expression was correlated substantially with the TNM stage, pathologic stage, smoking status, and effectiveness endpoints, when we analyzed its association with clinical characteristics in LUAD. Elevated NOP58 expression was shown as connected with Th2 cell infiltration while also negatively linked with infiltrating other immune cells, such as CD8 T, cytotoxic, and Th1. By inhibiting NOP58 within the LUAD cells, we found a decrease in cells' capability to proliferate, migrate, and invade. Knockdown of NOP58 inhibited tumor growth in mouse xenograft models. Furthermore, the tissue microarray study indicated that there was a greater expression of NOP58 in the tumor tissues compared to adjacent normal tissues in LUAD. Our findings revealed that NOP58 could be an outstanding bio-index for pan-cancer diagnosis and prognosis and an independent prognostic risk factor in LUAD.

Dysregulation of the DRAIC/SBK1 Axis Promotes Lung Cancer Progression

Background: Long non-coding RNAs (lncRNAs) are key regulators of cellular processes that underpin cancer development and progression. DRAIC is a migration inhibitor that has been linked with lung adenocarcinoma progression; however, its mechanisms remain to be studied. Methods: Several bioinformatics tools were used to explore the role of DRAIC in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Results: Our bioinformatics analysis illustrates that patients with low expression of DRAIC have poor overall survival outcomes. In addition, the mRNA of SH3 domain-binding kinase 1 (SBK1) was downregulated in this cohort of patients. Mechanistic analysis showed that SBK1 is under the DRAIC competing endogenous RNAs network, potentially through sponging of miRNA-92a. Conclusions: Consistent dysregulation of the DRAIC-SBK1 axis was linked to poor survival outcome in both LUAD and LUSC, suggesting a tumour inhibitor role and providing potential for new diagnostics and therapeutic approaches.

Reduced Risk of Severe Radiation-Induced Lymphopenia in Carbon Ion Radiation Therapy for Locally Advanced Pancreatic Cancer: A Comparative Analysis of Carbon Versus Photon Therapy

PURPOSE

Radiation-induced lymphopenia (RIL) is associated with poor prognosis in patients with locally advanced pancreatic cancers. However, there are no reports comparing the effects of carbon ion radiation therapy (CIRT) and photon beam radiation therapy (RT) on the development of RIL. Differences in RIL after CIRT or photon beam RT and predictive factors for RIL in patients with locally advanced pancreatic cancer were investigated.

MATERIALS AND METHODS

This retrospective study cohort included 834 patients who received concurrent chemoradiotherapy (CCRT) in 2 separate institutions: 337 and 497 in the CIRT and photon beam RT groups, respectively. Severe RIL was defined as an absolute lymphocyte count (ALC) <0.5 × 109 cells/L. A 1:1 propensity score-matching analysis was performed between the CIRT and photon beam RT groups. Patients were categorized into 3 groups according to the development of recovery from severe RIL: no severe RIL (Group A), recovery from severe RIL (Group B), and no recovery from severe RIL (Group C). Logistic regression analysis was performed to identify the predictive value of severe RIL. The prognostic factors of overall survival (OS) were determined using Cox regression analysis.

RESULTS

After propensity score matching, the baseline ALC and planning target volume of the CIRT and photon beam RT groups were comparable. During CCRT, the ALC of the entire cohort decreased and was significantly lower in the photon beam RT group than in the CIRT group (P < .001). Multivariate logistic regression analysis showed that CIRT reduced severe RIL more than photon beam RT. After adjusting for other factors, the RT modality and RIL were significantly associated with OS. Photon beam RT showed a significantly worse OS than CIRT, and Group C showed a significantly worse OS than Group A.

CONCLUSIONS

CIRT seems to reduce the development of severe RIL. The RT modality and development/recovery from severe RIL were associated with OS in patients who received CCRT for locally advanced pancreatic cancer. The reduction of severe RIL through optimized RT may be essential for improving treatment outcomes.

Effect of smoking on the diagnostic results and complication rates of percutaneous transthoracic needle biopsy

OBJECTIVE

To investigate the association of smoking with the outcomes of percutaneous transthoracic needle biopsy (PTNB).

METHODS

In total, 4668 PTNBs for pulmonary lesions were retrospectively identified. The associations of smoking status (never, former, current smokers) and smoking intensity (≤ 20, 21-40, > 40 pack-years) with diagnostic results (malignancy, non-diagnostic pathologies, and false-negative results in non-diagnostic pathologies) and complications (pneumothorax and hemoptysis) were assessed using multivariable logistic regression analysis.

RESULTS

Among the 4668 PTNBs (median age of the patients, 66 years [interquartile range, 58-74]; 2715 men), malignancies, non-diagnostic pathologies, and specific benign pathologies were identified in 3054 (65.4%), 1282 (27.5%), and 332 PTNBs (7.1%), respectively. False-negative results for malignancy occurred in 20.5% (236/1153) of non-diagnostic pathologies with decidable reference standards. Current smoking was associated with malignancy (adjusted odds ratio [OR], 1.31; 95% confidence interval [CI]: 1.02-1.69; p = 0.03) and false-negative results (OR, 2.64; 95% CI: 1.32-5.28; p = 0.006), while heavy smoking (> 40 pack-years) was associated with non-diagnostic pathologies (OR, 1.69; 95% CI: 1.19-2.40; p = 0.003) and false-negative results (OR, 2.12; 95% CI: 1.17-3.92; p = 0.02). Pneumothorax and hemoptysis occurred in 21.8% (1018/4668) and 10.6% (495/4668) of PTNBs, respectively. Heavy smoking was associated with pneumothorax (OR, 1.33; 95% CI: 1.01-1.74; p = 0.04), while heavy smoking (OR, 0.64; 95% CI: 0.40-0.99; p = 0.048) and current smoking (OR, 0.64; 95% CI: 0.42-0.96; p = 0.04) were inversely associated with hemoptysis.

CONCLUSION

Smoking history was associated with the outcomes of PTNBs. Current and heavy smoking increased false-negative results and changed the complication rates of PTNBs.

CLINICAL RELEVANCE STATEMENT

Smoking status and intensity were independently associated with the outcomes of PTNBs. Non-diagnostic pathologies should be interpreted cautiously in current or heavy smokers. A patient's smoking history should be ascertained before PTNB to predict and manage complications.

KEY POINTS

• Smoking status and intensity might independently contribute to the diagnostic results and complications of PTNBs. • Current and heavy smoking (> 40 pack-years) were independently associated with the outcomes of PTNBs. • Operators need to recognize the association between smoking history and the outcomes of PTNBs.

Recent advances in sialic acid-based active targeting chemoimmunotherapy promoting tumor shedding: a systematic review

Tumors have always been a major public health concern worldwide, and attempts to look for effective treatments have never ceased. Sialic acid is known to be a crucial element for tumor development and its receptors are highly expressed on tumor-associated immune cells, which perform significant roles in establishing the immunosuppressive tumor microenvironment and further boosting tumorigenesis, progression, and metastasis. Obviously, it is essential to consider sophisticated crosstalk between tumors, the immune system, and preparations, and understand the links between pharmaceutics and immunology. Sialic acid-based chemoimmunotherapy enables active targeting drug delivery via mediating the recognition between the sialic acid-modified nano-drug delivery system represented by liposomes and sialic acid-binding receptors on tumor-associated immune cells, which inhibit their activity and utilize their homing ability to deliver drugs. Such a "Trojan horse" strategy has remarkably improved the shortcomings of traditional passive targeting treatments, unexpectedly promoted tumor shedding, and persistently induced robust immunological memory, thus highlighting its prospective application potential for targeting various tumors. Herein, we review recent advances in sialic acid-based active targeting chemoimmunotherapy to promote tumor shedding, summarize the current viewpoints on the tumor shedding mechanism, especially the formation of durable immunological memory, and analyze the challenges and opportunities of this attractive approach.

Research trends in lung cancer and the tumor microenvironment: a bibliometric analysis of studies published from 2014 to 2023

Background

Lung cancer (LC) is one of the most common malignant tumors in the world and the leading cause of cancer-related deaths, which seriously threatens human life and health as well as brings a heavy burden to the society. In recent years, the tumor microenvironment (TME) has become an emerging research field and hotspot affecting tumor pathogenesis and therapeutic approaches. However, to date, there has been no bibliometric analysis of lung cancer and the tumor microenvironment from 2014 to 2023.This study aims to comprehensively summarize the current situation and development trends in the field from a bibliometric perspective.

Methods

The publications about lung cancer and the tumor microenvironment from 2014 to 2023 were extracted from the Web of Science Core Collection (WoSCC). The Microsoft Excel, Origin, R-bibliometrix, CiteSpace, and VOSviewer software are comprehensively used to scientifically analyze the data.

Results

Totally, 763 publications were identified in this study. A rapid increase in the number of publications was observed after 2018. More than 400 organizations published these publications in 36 countries or regions. China and the United States have significant influence in this field. Zhou, CC and Frontiers in Immunology are the most productive authors and journals respectively. Besides, the most frequently cited references were those on lung cancer pathogenesis, clinical trials, and treatment modalities. It suggests that novel lung cancer treatment models mainly based on the TME components, such as cancer-associated fibroblasts (CAFs) may lead to future research trends.

Conclusions

The field of lung cancer and the tumor microenvironment research is still in the beginning stages. Gene expression, molecular pathways, therapeutic modalities, and novel detection technologies in this field have been widely studied by researchers. This is the first bibliometric study to comprehensively summarize the research trend and development regarding lung cancer and tumor microenvironment over the last decade. The result of our research provides the updated perspective for scholars to understand the key information and cutting-edge hotspots in this field, as well as to identify future research directions.

A Nomogram Based on Platelet Distribution Width-to-Lymphocyte Ratio to Predict Overall Survival in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma

Purpose

To evaluate the prognostic significance of platelet distribution width-to-lymphocyte ratio (PDWLR) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC). Moreover, a nomogram based on PDWLR was built and validated to predict the overall survival (OS) of this population.

Patients and Methods

All LA-NPC patients who were diagnosed and treated between January 2015 and December 2017 at Guangxi Medical University Cancer Hospital were included. Cox regression analyses were performed to assess PDWLR and clinical features that might affect OS to screen for independent predictors. The independent predictors and important clinical variables were used to build and validate a nomogram for predicting OS. Then, the capability of the model was estimated by discrimination, calibration and clinical usefulness. Risk stratification was conducted using the nomogram-calculated risk score, and the comparison of survival in the high-risk group and the low-risk group was through Kaplan-Meier method.

Results

This study included 746 LA-NPC patients. Multivariate Cox analysis suggested that age (hazard ratio [HR]: 1.81, 95% confidence interval [CI]: 1.18-2.78, P = 0.007), gender (HR: 2.03, 95% CI: 1.12-3.68, P = 0.019), pre-treatment plasma Epstein-Barr virus (EBV) DNA (HR: 1.55, 95% CI: 1.01-2.39, P = 0.047), PDWLR (HR: 2.61, 95% CI: 1.67-4.09, P < 0.001) were independent predictors of OS. Compared to the 8th edition TNM staging system, the nomogram based on the above four factors and important clinical variables (T stage and N stage) demonstrated better predictive performance. Moreover, the model had the ability to identify individuals at high risk.

Conclusion

PDWLR was a promising negative predictor for patients with LA-NPC. The nomogram based on PDWLR demonstrated better predictive performance than the current staging system.

B7-H3 and ICAM-1 are potentially therapeutic targets for thyroid carcinoma

Although most differentiated thyroid carcinoma has a clinically favorable prognosis, some of specific types of thyroid cancer (such as anaplastic thyroid carcinoma and advanced papillary thyroid carcinoma) show fatal outcomes and require novel treatments. Immunotherapy is a promising avenue for the treatment of advanced thyroid carcinoma. B7-H3 (B7 homolog 3 protein) and ICAM-1 (intercellular adhesion molecule 1), as two important immune checkpoints (ICPs), is becoming hopeful target spots for immunotherapy. A growing amount of evidence has suggested that B7-H3 and ICAM-1 are upregulated in papillary thyroid carcinoma. However, their expression level in specific types of thyroid cancer remains largely unclear. In the present study, we explored the expression level of B7-H3 and ICAM-1 in different types of thyroid carcinoma. In the groups of the TCGA cohort, both B7-H3 and ICAM-1 mRNA were highly expressed in thyroid carcinoma. Furthermore, the patients with Stage2, 61-80y, Follicular thyroid papillary carcinoma and N0 had lower B7-H3 and ICAM-1 mRNA expression. In the groups of our cohort, PTCs and ATCs showed frequently moderate to strong expression of B7-H3 and ICAM-1 protein expression. The significant relevance of B7-H3 staining score with ICAM-1 staining score was observed in TCGA database and our cohort, which might open avenues for the combination therapy in advanced thyroid cancer.

Tumorigenic role of Pak4 in ovarian cancer and its correlation with immune infiltration

BACKGROUND

Ovarian cancer is the most common cause of gynecological cancer death. Pak4 has been proved to be tumorigenic in many types of cancers, but its role in ovarian cancer is still not clarified.

METHODS

In this study, we used immunohistochemistry to investigate into Pak4 expression in different histological types of ovarian cancer. TIMER, TISCH2, GEPIA, ualcan, KM plotter, GSCA and GeneMANIA were used to identify the prognostic roles and gene regulation networks of Pak4 in ovarian cancer. Immune infiltration levels were investigated using TIMER database.

RESULTS

Pak4 was highly expressed in ovarian cancers, regardless of different FIGO stages and histological grades. Single cell sequencing database proved that Pak4 was highly expressed in malignant ovarian cancer cells. Pak4 level was significantly correlated with different histological types of ovarian cancer. Pak4 expression was negatively connected with OS and PFS of ovarian cancer patients. Functions of Pak4 and its interacted genes were mainly involved in protein serine/threonine kinase activity, regulation of actin filament-based process and regulation of cytoskeleton organization. Pak4 level was negatively correlated with immune biomarkers of B cell infiltration (p = 2.39e-05), CD8 + T cell infiltration (p = 1.51e-04), neutrophil (p = 1.74e-06) and dendritic cell (p = 4.41e-08). Close correlation was found between Pak4 expression and T cell exhaustion (p < 0.05).

CONCLUSIONS

Our results demonstrated the expression level, gene interaction networks and immune infiltration levels of Pak4 in ovarian cancer. And the results revealed role of Pak4 in tumorigenesis and the possibility to be a potential immunotherapeutic target.

Potential mechanism of Chai Gui Zexie Decoction for NSCLC treatment assessed using network pharmacology, bioinformatics, and molecular docking: An observational study

To explore the potential mechanism of Chai Gui Zexie Decoction for non-small cell lung cancer (NSCLC) treatment using network pharmacology, bioinformatics, and molecular docking. The active ingredients of Chai Gui Zexie Decoction and the associated predicted targets were screened using the TCMSP database. NSCLC-related targets were obtained from GeneCards and OMIM. Potential action targets, which are intersecting drug-predicted targets and disease targets, were obtained from Venny 2.1. The protein-protein interaction network was constructed by importing potential action targets into the STRING database, and the core action targets and core ingredients were obtained via topological analysis. The core action targets were entered into the Metascape database, and Gene Ontology annotation analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Differentially expressed genes were screened using the Gene Expression Omnibus, and the key targets were obtained by validating the core action targets. The key targets were input into The Tumor IMmune Estimation Resource for immune cell infiltration analysis. Finally, the molecular docking of key targets and core ingredients was performed. We obtained 60 active ingredients, 251 drug prediction targets, and 2133 NSCLC-related targets. Meanwhile, 147 potential action targets were obtained, and 47 core action targets and 40 core ingredients were obtained via topological analysis. We detected 175 pathways related to NSCLC pharmaceutical therapy. In total, 1249 Gene Ontology items were evaluated. Additionally, 3102 differential genes were screened, and tumor protein P53, Jun proto-oncogene, interleukin-6, and mitogen-activated protein kinase 3 were identified as the key targets. The expression of these key targets in NSCLC was correlated with macrophage, CD4+ T, CD8+ T, dendritic cell, and neutrophil infiltration. The molecular docking results revealed that the core ingredients have a potent affinity for the key targets. Chai Gui Zexie Decoction might exert its therapeutic effect on NSCLC through multiple ingredients, targets, and signaling pathways.

SCIPAC: quantitative estimation of cell-phenotype associations

Numerous algorithms have been proposed to identify cell types in single-cell RNA sequencing data, yet a fundamental problem remains: determining associations between cells and phenotypes such as cancer. We develop SCIPAC, the first algorithm that quantitatively estimates the association between each cell in single-cell data and a phenotype. SCIPAC also provides a p-value for each association and applies to data with virtually any type of phenotype. We demonstrate SCIPAC's accuracy in simulated data. On four real cancerous or noncancerous datasets, insights from SCIPAC help interpret the data and generate new hypotheses. SCIPAC requires minimum tuning and is computationally very fast.

VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology

In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques necessitate the need for labels, providing manual cell annotations is time-consuming. In this paper, we propose a self-supervised framework (enVironment-aware cOntrastive cell represenTation learning: VOLTA) for cell representation learning in histopathology images using a technique that accounts for the cell's mutual relationship with its environment. We subject our model to extensive experiments on data collected from multiple institutions comprising over 800,000 cells and six cancer types. To showcase the potential of our proposed framework, we apply VOLTA to ovarian and endometrial cancers and demonstrate that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised models, we provide a framework that can empower discoveries without any annotation data, even in situations where sample sizes are limited.

Prognostic significance of T lymphocyte subgroups (CD4 and CD8) in lung cancer patients after neoadjuvant chemotherapy

OBJECTIVE

The basis for current and future lung cancer immunotherapy depends on our knowledge of molecular mechanisms of interactions between tumor and immune system cells. Interactions that occur between different intratumoral populations of the same cells are important. In our study, we aimed to evaluate relationship between the clinical and prognostic features and T lymphocyte subgroups of patients with lung tumors after neoadjuvant treatment.

METHODS

A total of 72 patients were included in our study, including study group, 39 of whom received neoadjuvant chemotherapy. Clinical/radiological/pathological findings of patients and CD4/CD8 staining rates in peritumoral/intratumoral areas were recorded.

RESULTS

Our study revealed significantly lower intratumoral CD4 + T cell density and lower intratumoral CD4/CD8 ratio in primary tumor after neoadjuvant therapy (respectively, 0.012 and 0.016). Considering tumor types, when control-study groups were compared, inflammation was statistically significant only in adenocarcinoma subtype; intratumoral CD4/CD8 ratio was statistically significant only in squamous-cell carcinoma subtype (respectively, p = 0.0008 and p = 0.0139). When CD4 + T lymphocytes and CD8 + T lymphocytes and CD4/CD8 ratio were compared between control and study groups in low-stage patients according to clinical stages, only intratumoral CD4 + T lymphocyte values and intratumoral CD4/CD8 ratio were significant (respectively, p = 0.0291 ve p = 0.0154).

CONCLUSION

All cell types of innate and adaptive intratumoral immunity can affect lung cancer tissues simultaneously, and these interactions have a very complex structure. Understanding the tumor microenvironment and the different roles of associated cancer immune cells may lead to the discovery of new targets for immunological therapies and increased survival times in lung cancer.

Comprehensive analysis of the effects of the cuprotosis-associated gene SLC31A1 on patient prognosis and tumor microenvironment in human cancer

BACKGROUND

Solute carrier family 31 (copper transporter), member 1 (SLC31A1) is a key factor in maintaining intracellular copper concentration and an important factor affecting cancer energy metabolism. Therefore, exploring the potential biological function and value of SLC31A1 could provide a new direction for the targeted therapy of tumors.

METHODS

This study assessed gene expression levels, survival, clinicopathology, gene mutations, methylation levels, the tumor mutational burden (TMB), microsatellite instability (MSI), and the immune cell infiltration of SLC31A1 in pan-cancer using the Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham CANcer (UALCAN) data analysis portal, and cBioPortal databases. To further understand the potential biological mechanisms of SLC31A1 in different cancers, single-cell level sequencing and a Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis of SLC31A1 were also performed. Finally, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting (WB) were used to validate the expression of SLC31A1 in cancers, such as gastric cancer.

RESULTS

SLC31A1 was expressed in most cancer tissues. In kidney renal clear cell carcinoma (KIRC), the high expression of SLC31A1 was associated with good overall survival (OS), while in adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), lower grade glioma (LGG), mesothelioma (MESO), and skin cutaneous melanoma (SKCM), the low expression of SLC31A1 was associated with good OS. The highest frequency of SLC31A1 amplification was observed in ACC. In addition, missense mutations accounted for a major portion of the mutation types. The truncation mutation S105Y may be a putative cancer driver. SLC31A1 affected methylation levels in cancer and was associated with the TMB, MSI, and the level of infiltration of various immune cells. Additionally, the single-cell sequencing results showed that SLC31A1 was associated with multiple biological functions in cancer. Finally, the SLC31A1 enrichment analysis revealed that the SLC31A1-related genes were mainly enriched in the mitochondrial matrix and envelope vesicles. The RT-qPCR and WB results were consistent with the predicted results.

CONCLUSIONS

SLC31A1 may be a potential target related to cancer energy metabolism and may have prognostic value.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

PLAU and GREM1 are prognostic biomarkers for predicting immune response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan-Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.

Prognostic significance of initial tumor shrinkage in patients with stage III non-small cell lung cancer treated with durvalumab following chemoradiotherapy

BACKGROUND

Baseline tumor size (BTS) is one of the prognostic factors of advanced non-small cell lung cancer (NSCLC) treated with immunotherapy. However, its prognostic value in patients with locally advanced NSCLC receiving durvalumab maintenance therapy remains unclear.

METHODS

The present study retrospectively reviewed 136 patients with unresectable stage III NSCLC who underwent CRT and durvalumab at two institutions in Japan. The maximum diameter of the target lesion (max BTS) before CRT was measured, the best response to CRT before durvalumab was evaluated, and the impact of the response on durvalumab was explored. Progression-free survival (PFS) and overall survival (OS) were defined as the time from the day of starting durvalumab.

RESULTS

Of the total cohort, 133 (97.8%) patients had at least one measurable lesion. The best response to CRT resulting in CR, PR, and SD was seen in 0 (0%), 69 (51.9%), and 64 (48.1%) patients, respectively. PFS was significantly longer in the patients with PR than in those with SD after CRT (median not reached vs. 20.0 months; HR: 0.51; P = 0.023). Moreover, the absence of a massive lesion (max BTS < 50 mm) was associated with a superior CRT response (P < 0.001).

CONCLUSION

The best response to induction CRT was associated with better PFS in patients with stage III NSCLC receiving durvalumab following chemoradiotherapy. Although the absence of a massive lesion was associated with a better response to induction CRT in this cohort, this was not translated into PFS and OS benefit.

Insight into the significance of CD8+ tumor-infiltrating lymphocytes in squamous cell lung cancer

BACKGROUND

Although there are great expectations regarding the use of tumor-infiltrating lymphocytes (TILs) to predict effects of immunotherapies and prognosis, knowledge about TILs remains insufficient for clinical application.

METHODS

We objectively investigated the prognostic significance of tumor-infiltrating CD8 + lymphocytes (CD8 + TILs) in squamous cell lung cancer (SQ-LC). Among patients who underwent surgical resection of SQ-LC in 2011-2017, 100 patients with pathological stage IA3-III were immunohistochemically studied to evaluate CD8 + TILs in the tumor stroma and parenchyma. The impact of CD8 + TILs on relapse-free survival was analyzed using a Kaplan-Meier survival analysis and multivariate analyses using Fine-Gray and Cox proportional hazards models.

RESULTS

The multivariate analysis showed that large and small numbers, but not intermediate numbers, of CD8 + TILs in the tumor stroma may be related to a more favorable prognosis (small vs. intermediate: HR, 0.64; 95% CI: 0.29-1.41, p = 0.27; large vs. intermediate: HR, 0.48; 95% CI: 0.21-1.09, p = 0.08). In contrast, a large number of CD8 + TILs in the tumor parenchyma was associated with a poor prognosis (HR, 2.60; 95% CI: 0.91-7.42, p = 0.075). An exploratory analysis showed a potentially strong association between an extremely large number of CD8 + TILs in the tumor parenchyma and a poor prognosis, even with a large number of CD8 + TILs in the tumor stroma.

CONCLUSION

Our study provided partial but important information on the significance of CD8 + TILs in SQ-LC. To use CD8 + TILs as biomarkers, a better understanding of CD8 + TILs as well as other important components in the tumor microenvironment and the inflammatory phenotypes they form may be needed.

RLP system: A single-tube two-step approach with dual amplification cascades for rapid identification of EGFR T790M

BACKGROUND

The detection of cancer gene mutations in biofluids plays a pivotal role in revolutionizing disease diagnosis. The presence of a large background of wild-type sequences poses a challenge to liquid biopsy of tumor mutation genes. Suppressing the detection of wild-type sequences can reduce their interference, however, due to the minimal difference between mutant and wild-type sequences (such as single nucleotide variants differing by only one nucleotide), how to suppress the detection of wild-type sequences to the greatest extent without compromising the sensitivity of mutant sequence detection remains to be explored.

SIGNIFICANCE

The RLP system addresses the incompatibility between RPA and RT-PCR reactions through a physical separation strategy. Besides, due to the remarkable flexibility of locked nucleic acid probes, the RLP system emerges as a potent tool for detecting mutations across diverse genes. It excels in sensitivity and speed, tolerates plasma matrix, and is cost-effective. This bodes well for advancing the field of precision medicine.

RESULTS

The recombinase-assisted locked nucleic acid (LNA) probe-mediated dual amplification biosensing platform (namely RLP), which combines recombinase polymerase amplification (RPA) and LNA clamp PCR method in one tube, enabling highly sensitive and selective detection of EGFR T790M mutation under the help of well-designed LNA probes. This technique can quantify DNA targets with a limit of detection (LoD) at the single copy level and identify point mutation with mutant allelic fractions as low as 0.007 % in 45 min. Moreover, RLP has the potential for the direct detection of plasma samples without the need for nucleic acid extraction and the cost of a single test is less than 1USD. Furthermore, the RLP system is a cascading dual amplification reaction conducted in a single tube, which eliminates the risk of cross-contamination associated with opening multiple tubes and ensures the reliability of the results.

Genetic polymorphisms as potential pharmacogenetic biomarkers for platinum-based chemotherapy in non-small cell lung cancer

Platinum-based chemotherapy (PBC) is a widely used treatment for various solid tumors, including non-small cell lung cancer (NSCLC). However, its efficacy is often compromised by the emergence of drug resistance in patients. There is growing evidence that genetic variations may influence the susceptibility of NSCLC patients to develop resistance to PBC. Here, we provide a comprehensive overview of the mechanisms underlying platinum drug resistance and highlight the important role that genetic polymorphisms play in this process. This paper discussed the genetic variants that regulate DNA repair, cellular movement, drug transport, metabolic processing, and immune response, with a focus on their effects on response to PBC. The potential applications of these genetic polymorphisms as predictive indicators in clinical practice are explored, as are the challenges associated with their implementation.

Neutrophil-to-lymphocyte ratio is a prognostic factor reflecting immune condition of tumor microenvironment in squamous cell lung cancer

Inflammatory factors in the peripheral blood, such as the C-reactive protein level and neutrophil-to-lymphocyte ratio (NLR), are prognostic markers in multiple types of cancer, including non-small cell lung cancer (NSCLC). However, the association between inflammatory factors and prognosis based on histological types has not been adequately reported. In addition, the relationship between these factors and the immune condition of the tumor microenvironment (TME) is unclear. In this single center, retrospective study, we first investigated the relationship between preoperative inflammatory markers and clinical outcomes in 176 patients with NSCLC who underwent surgery. Lung adenocarcinoma (LUAD) showed no significant prognostic marker, whereas for lung squamous cell carcinoma (LUSC), a multivariate analysis showed that a high NLR was significantly associated with postoperative recurrence. In LUSC patients, the median time of postoperative recurrence-free survival in patients with a low NLR was longer than that in patients with a high NLR. We then compared the tumor-infiltrating lymphocyte (TIL) profile with inflammatory markers in peripheral blood and found that the NLR was negatively correlated with the frequencies of T cells and B cells in LUSC tissues. Thus, the NLR is a useful predictive biomarker for postoperative recurrence and may reflect the immune condition of the TME in LUSC.

Development and validation of an individualized angiogenesis and tumor-infiltrating lymphocytes prognostic signature in nasopharyngeal carcinoma

In recent years, targeted therapy and immunotherapy have become ideal choices for the treatment of advanced, metastatic, recurrent, and drug-resistant nasopharyngeal carcinoma (NPC), but the lack of understanding of the relationship and mechanism between TILs and angiogenic factors hinders therapeutic development and optimization. In this study, the expression of angiogenesis-related markers (VEGF-A,VEGFR-2) and TILs (CD4+T,CD8+T) was studied by using immunohistochemistry (IHC). Then we constructed an immunohistochemical scoring model for the co-expression of angiogenesis-related markers and TILs (COV+TIL score)in the training (n = 124) and validated the accuracy and reliability of the scoring system in the validation cohorts (n = 114), respectively We established the COV+TIL score model and stratified patients into different risk level in the training cohorts according to COV+TIL score (cut-off value=28). Patients in the high-risk group had worse prognosis in the training cohorts five-year overall survival (OS), progression-free survival (PFS), locoregional relapse-free survival (LRRFS), and distant metastasis-free survival (DMFS) was lower than that of patients in the low-risk group, and this result was validated in the validation cohorts ( 5-year OS in the high-risk and the low-risk group 46.8% vs. 83.4%, HR: 3.42, 95%CI: 1.77-6.61, p < 0.001); ( 5-year PFS 45.9% vs. 81.2%, HR: 3.22, 95%CI: 1.71-6.06, p < 0.001); ( 5-year LRRFS 74.6% vs. 87.5%, HR: 3.22, 95%CI: 1.16-8.93, p = 0.027); and ( 5-year DMFS79.2% vs. 93.2%, HR: 2.22, 95%CI: 0.91-5.39, p = 0.086). Upon multivariable analysis, COV+TIL score emerged as an independent prognostic indicator for defining survival in the training cohorts and the validation cohorts. Combining the COV+TIL score and TNM stage improved the prediction ability of the survival. In conclusion, NPC patients with high COV+TIL score showed worse prognosis.

Particle filter-based parameter estimation algorithm for prognostic risk assessment of progression in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a malignant tumor that threatens human life and health. The development of a new NSCLC risk assessment model based on electronic medical records has great potential for reducing the risk of cancer recurrence. In this process, machine learning is a powerful method for automatically extracting risk factors and indicating impact weights for NSCLC deaths. However, when the number of samples reaches a certain value, it is difficult for machine learning to improve the prediction accuracy, and it is also challenging to use the characteristic data of subsequent patients effectively. Therefore, this study aimed to build a postoperative survival risk assessment model for patients with NSCLC that updates the model parameters and improves model accuracy based on new patient data. The model perspective was a combination of particle filtering and parameter estimation. To demonstrate the feasibility and further evaluate the performance of our approach, we performed an empirical analysis experiment. The study showed that our method achieved an overall accuracy of 92% and a recall of 71% for deceased patients. Compared with traditional machine learning models, the accuracy of the model estimated by particle filter parameters has been improved by 2%, and the recall rate for dead patients has been improved by 11%. Additionally, this study outcome shows that this method can better utilize subsequent patients' characteristic data, be more relevant to different patients, and help achieve precision medicine.

Mutations in the DNA polymerase binding pathway affect the immune microenvironment of patients with small-cell lung cancer and enhance the efficacy of platinum-based chemotherapy

Background

Small-cell lung cancer (SCLC) is characterized by its high malignancy and is associated with a poor prognosis. In the early stages of the disease, platinum-based chemotherapy is the recommended first-line treatment and has demonstrated efficacy. However, SCLC is prone to recurrence and is generally resistant to chemotherapy in its later stages.

Methods

Here, we collected samples from SCLC patients who received platinum-based chemotherapy, performed genomic and transcriptomic analyses, and validated our results with publicly available data.

Results

SCLC patients with DNA polymerase binding pathway mutations had an improved prognosis after platinum chemotherapy compared with patients without such mutations. Patients in the mutant (MT) group had higher infiltration of T cells, B cells, and M1 macrophages compared with patients without DNA polymerase binding pathway mutations.

Conclusions

DNA polymerase binding pathway mutations can be used as prognostic markers for platinum-based chemotherapy in SCLC.

YAP1/Piezo1 involve in the dynamic changes of lymphatic vessels in UVR-induced photoaging progress to squamous cell carcinoma

BACKGROUND

UV-induced cutaneous squamous cell carcinoma (cSCC) is one of the most common skin cancers. The constant alterations of the lymphatic-centered immune microenvironment are essential in transforming from photoaging to cSCC. Studying the mechanism will be beneficial for new targets exploration to the early prediction of cSCC.

AIMS

To investigate the dynamic changes and mechanism of the lymphatic-centered immune microenvironment in transforming from photoaging to cSCC induced by ultraviolet irradiation (UVR).

METHODS

TIMER2.0 was used to analyze whether YAP1/VEGFC signaling pathway is involved in lymphangiogenesis in head and neck squamous cell carcinoma (HNSCC). Meanwhile, lymphatic-centered immune microenvironments alterations and the related cumulative survival time were also analyzed. With the accumulated UVR, skin photoaging developed and gradually progressed into actinic keratosis and cSCC on SKH-1 hairless mice. The skin lymphatic-centered immune microenvironment was evaluated at the 0th, 8th, 12th, 16-18th, and 20-24th week of UVR. Skin phenotype was assessed using optical coherence tomography (OCT) and skin image. H&E and Masson's trichrome staining evaluated epidermis and dermis. The structure of lymphatic vessels (LVs), blood vessels, and different types of T cells were evaluated by immunohistochemistry staining. The expression of Piezo1 whose deletion in adult lymphatics led to substantial valve degeneration, VE-cadherin that maintained the permeability of LVs, and YAP1 were evaluated by immunohistochemistry staining as well. Besides, the drainage function of LVs was assessed by Evans Blue assay in vivo.

RESULTS

The lymphatic function and immune cell infiltration underwent adaptive changes under continuous UVR. TIMER2.0 analysis indicated that VEGFC genes high expressed in HNSCC. YAP1 gene expression was positive correlated with VEGFC in HNSCC. LV density increased in human cSCC. More LVs in HNSCC were beneficial to prolong the survival time. VEGFC gene overexpression was positive correlated to CD8+T cell infiltration. More CD8A+T cells and CD8B+T cell infiltration in HNSCC extended survival time. When YAP1 gene overexpression and high infiltration of endothelial cells took place simultaneously might prolong the survival time of HNSCC patients. And high infiltration of CD8+T cells prolonged the survival time as well. In animal studies, UVR-induced eight weeks (photoaging) and 16-18 weeks (precancerous) were two turning points. The density of LVs in UV-8w was the least. When photoaged skin developed into AK lesions (UV-16-18w), LV slightly exceeded healthy skin and proliferated sharply in cSCC (UV-20-24w). YAP1 expression was almost consistent with LV but rose after the photoaging stage. The drainage of cSCC mice induced by UVR was better than that of photoaged skin and worse than that of health skin. The dynamic alterations of LVs number, Piezo1 expression, and collagen might be reasons for it. The expression of Piezo1 was in the highest point after 8 weeks of UVR, then gradually descended to the platform. The total T cells increased slowly, but the infiltration of CD4+T cells increased, and CD8+T cells decreased after eight weeks of UVR. The CD8+T cells and CD4+T cells increased sharply in UV-16-18w and UV-20-24w groups.

CONCLUSION

The lymphatic-centered immune microenvironment underwent adaptive changes under continuous UVR via regulating YAP1/VEGFC and Piezo1. During the formation of cSCC, there are two turning points, eight weeks (photoaging) and 16-18 weeks (precancerous). YAP1, Piezo1, LVs, and immune cells constantly changed with the skin state induced by UVR. According to these changes the process of cSCC can be identified in advance and intervene timely.

Prognostic significance of tumor microenvironment assessed by machine learning algorithm in surgically resected non-small cell lung cancer

BACKGROUND

A methodology to assess the immune microenvironment (IME) of non-small cell lung cancer (NSCLC) has not been established, and the prognostic impact of IME factors is not yet clear.

AIMS

This study aimed to assess the IME factors and evaluate their prognostic values.

METHODS AND RESULTS

We assessed CD8+ tumor-infiltrating lymphocyte (TIL) density, forkhead box protein P3+ (Foxp3+ ) TIL density, and programmed death receptor ligand-1 (PD-L1) tumor proportion score (TPS) using a machine-learning algorithm in whole-slide imaging (WSI). We dichotomized patients according to TIL density or TPS and compared their clinical outcomes. Between September 2014 and September 2015, 165 patients with NSCLC were enrolled in the study. We assessed IME factors in the epithelium, stroma, and their combination. An improvement in disease-free survival (DFS) was observed in the high CD8+ TIL density group in the epithelium, stroma, and the combination of both. Moreover, the group with high PD-L1 TPS in the epithelium showed better DFS than that with low PD-L1 TPS. In the multivariate analysis, the CD8+ TIL density in the combination of epithelium and stroma and PD-L1 TPS in the epithelium were independent prognostic factors (hazard ratio [HR] = 0.43; 95% confidence interval [CI] = 0.26-0.72; p = .001, HR = 0.49; 95% CI = 0.30-0.81; p = .005, respectively).

CONCLUSION

Our approach demonstrated that the IME factors are related to survival in patients with NSCLC. The quantitative assessment of IME factors enables to discriminate patients with high risk of recurrence, who can be the candidates for adjuvant therapy. Assessing the CD8+ TIL density in the combination of epithelium and stroma might be more useful than their individual assessment because it is a simple and time-saving analysis of TILs in WSI.

Identification of pyroptosis-related lncRNA subtype and signature predicts the prognosis in bladder cancer

Pyroptosis is a new type of programmed cell death involved in all stages of tumorigenesis. Herein, a comprehensive study was conducted to evaluate the prognostic significance of pyroptosis-related lncRNAs in bladder cancer. Consensus clustering analysis was performed to identify the subclusters of bladder cancer. The prognostic pyroptosis-related lncRNA signature was constructed using LASSO Cox regression analysis. Consensus clustering identified 2 clusters of bladder cancer. Interestingly, significant differences in the ESTIMAE score, immune cell infiltration and immune checkpoint expression were obtained between the 2 clusters. A signature consisting of 11 pyroptosis-related lncRNAs was established and it had a good performance in predicting the overall survival rate of bladder cancer, with an AUC of 0.713. Moreover, pyroptosis-related lncRNA signature acted as a risk factor in bladder cancer. Bladder cancer patients with high-risk score had a higher tumor grade and higher clinical stage. A significant correlation was obtained between the risk score and immune cell infiltration. The expression of most checkpoints was higher in bladder cancer patients with high-risk score. A novel pyroptosis-related lncRNA signature was identified with prognostic value for bladder cancer patients. Pyroptosis-related lncRNAs have a potential role in cancer immunology and may serve as prognostic or therapeutic targets in bladder cancer.

Advances in immunotyping of colorectal cancer

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies.

Collagen code in tumor microenvironment: Functions, molecular mechanisms, and therapeutic implications

The tumor microenvironment (TME) is crucial in cancer progression, and the extracellular matrix (ECM) is an important TME component. Collagen is a major ECM component that contributes to tumor cell infiltration, expansion, and distant metastasis during cancer progression. Recent studies reported that collagen is deposited in the TME to form a collagen wall along which tumor cells can infiltrate and prevent drugs from working on the tumor cells. Collagen-tumor cell interaction is complex and requires the activation of multiple signaling pathways for biochemical and mechanical signaling interventions. In this review, we examine the effect of collagen deposition in the TME on tumor progression and discuss the interaction between collagen and tumor cells. This review aims to illustrate the functions and mechanisms of collagen in tumor progression in the TME and its role in tumor therapy. The findings indicated collagen in the TME appears to be a better target for cancer therapy.

Prognosis and immunoinfiltration analysis of angiogene-related genes in grade 4 diffuse gliomas

Although angiogenesis critically influences the progression of solid tumors, its contribution to highly malignant, grade 4 diffuse gliomas remains unclear. After analyzing 506 angiogenesis-related genes differentially expressed in grade 4 diffuse gliomas via LASSO and univariate and multivariate COX regression analyses, we constructed a nomogram based on COL22A1, IGFBP2, and MPO that accurately predicted patient survival. The nomogram's performance was validated in an external patient cohort, and a risk score based on the formula COL22A1*0.148+IGFBP2*0.234+MPO*0.145 was used to distinguish high-risk from low-risk patients. Based on differentially expressed genes among risk groups, functional enrichment and drug sensitivity analyses were conducted, and the association between COL22A1, IGFBP2, and MPO expression and infiltrating immune cells and immune checkpoint genes was investigated. We next focused on COL22A1, and verified its overexpression in both glioma cell lines and clinical samples. A pro-oncogenic role for COL22A1, evidenced by impaired proliferation, migration, and invasion capacities, was evidenced upon shRNA-mediated COL22A1 silencing in glioma U87 and LN18 cells. In summary, we present a novel nomogram based on the angiogenesis-related genes COL22A1, IGFBP2, and MPO that allows survival prediction in patients with grade 4 diffuse gliomas. Furthermore, our cellular assays support a pro-oncogenic role for COL22A1 in these tumors.

Comprehensive analysis of the prognostic values and immune implication of ESYT3 in lung adenocarcinoma

Few studies have reported the association between ESYT3 and tumors. The purpose of this study was to investigate the molecular features and potential roles of ESYT3 in lung adenocarcinoma (LUAD). In the present study, GEPIA, UALCAN, TCGA databases, and KM Plotter were primarily used to study ESYT3 mRNA expression profiles and prognostic values in patients with LUAD. Then we evaluated co-expressed genes of ESYT3 by cBioPortal online tools and performed enrichment analysis using Metascape. Moreover, the relationship between ESYT3 and immune infiltrating cells was explored via TIMER2, and MethSurv database was used to conduct methylation analysis. We found ESYT3 was downregulated in LUAD tissues based on TCGA and GEPIA databases. Low expression of ESYT3 mRNA was observed to be significantly correlated with N classification and stage classification. GEPIA2, UALCAN databases and KM Plotter showed that low expression levels of ESYT3 was associated with poor survival in LUAD patients. The enrichment analysis indicated that co-expressed genes of ESYT3 were highly enriched in cell division. Then, our study showed ESYT3 was correlated with immune infiltration and immune checkpoints. Additionally, hypomethylation was associated with low ESYT3 expression and poor prognosis in LUAD. In conclusion, this study suggested ESYT3 could be a potential prognostic marker and a promising therapeutic target in LUAD.

Immune Infiltration in Tumor and Adjacent Non-Neoplastic Regions Codetermines Patient Clinical Outcomes in Early-Stage Lung Cancer

INTRODUCTION

In recent years, the proportion of patients with NSCLC diagnosed at an early stage has increased continuously.

METHODS

In this study, we analyzed samples and data collected from 119 samples from 67 early stage patients with NSCLC, including 52 pairs of tumor and adjacent non-neoplastic samples, and performed RNA-sequencing analysis with high sequencing depth.

RESULTS

We found that immune-related genes were highly enriched among the differentially expressed genes and observed significantly higher inferred immune infiltration levels in adjacent non-neoplastic samples than in tumor samples. In survival analysis, the infiltration of certain immune cell types in tumor, but not adjacent non-neoplastic, samples were associated with overall patient survival, and excitingly, the differential infiltration between paired samples (tumor minus non-neoplastic) was more prognostic than expression in either non-neoplastic or tumor tissues. We also performed B cell receptor (BCR) and T cell receptor (TCR) repertoire analysis and observed more BCR/TCR clonotypes and increased BCR clonality in tumor than in non-neoplastic samples. Finally, we carefully quantified the fraction of the five histologic subtypes in our adenocarcinoma samples and found that higher histologic pattern complexity was associated with higher immune infiltration and low TCR clonality in the tumor-proximal regions.

CONCLUSIONS

Our results indicated significantly differential immune characteristics between tumor and adjacent non-neoplastic samples and suggested that the two regions provided complementary prognostic values in early-stage NSCLCs.

Revealing the role of regulatory T cells in the tumor microenvironment of lung adenocarcinoma: a novel prognostic and immunotherapeutic signature

Background

Regulatory T cells (Tregs), are a key class of cell types in the immune system. In the tumor microenvironment (TME), the presence of Tregs has important implications for immune response and tumor development. Relatively little is known about the role of Tregs in lung adenocarcinoma (LUAD).

Methods

Tregs were identified using but single-cell RNA sequencing (scRNA-seq) analysis and interactions between Tregs and other cells in the TME were investigated. Next, we used multiple bulk RNA-seq datasets to construct risk models based on marker genes of Tregs and explored differences in prognosis, mutational landscape, immune cell infiltration and immunotherapy between high- and low-risk groups, and finally, qRT-PCR and cell function experiments were performed to validate the model genes.

Results

The cellchat analysis showed that MIF-(CD74+CXCR4) pairs play a key role in the interaction of Tregs with other cell subpopulations, and the Tregs-associated signatures (TRAS) could well classify multiple LUAD cohorts into high- and low-risk groups. Immunotherapy may offer greater potential benefits to the low-risk group, as indicated by their superior survival, increased infiltration of immune cells, and heightened expression of immune checkpoints. Finally, the experiment verified that the model genes LTB and PTTG1 were relatively highly expressed in cancer tissues, while PTPRC was relatively highly expressed in paracancerous tissues. Colony Formation assay confirmed that knockdown of PTTG1 reduced the proliferation ability of LUAD cells.

Conclusion

TRAS were constructed using scRNA-seq and bulk RNA-seq to distinguish patient risk subgroups, which may provide assistance in the clinical management of LUAD patients.

The identification of genes associated T-cell exhaustion and construction of prognostic signature to predict immunotherapy response in lung adenocarcinoma

T-cell exhaustion (Tex) is considered to be a reason for immunotherapy resistance and poor prognosis in lung adenocarcinoma. Therefore, we used weighted correlation network analysis to identify Tex-related genes in the cancer genome atlas (TCGA). Unsupervised clustering approach based on Tex-related genes divided patients into cluster 1 and cluster 2. Then, we utilized random forest and the least absolute shrinkage and selection operator to identify nine key genes to construct a riskscore. Patients were classified as low or high-risk groups. The multivariate cox analysis showed the riskscore was an independent prognostic factor in TCGA and GSE72094 cohorts. Moreover, patients in cluster 2 with high riskscore had the worst prognosis. The immune response prediction analysis showed the low-risk group had higher immune, stromal, estimate scores, higher immunophenscore (IPS), and lower tumor immune dysfunction and exclusion score which suggested a better response to immune checkpoint inhibitors (ICIs) therapy in the low-risk group. In the meantime, we included two independent immunotherapy cohorts that also confirmed a better response to ICIs treatment in the low-risk group. Besides, we discovered differences in chemotherapy and targeted drug sensitivity between two groups. Finally, a nomogram was built to facilitate clinical decision making.

Comprehensive analysis of the role of a four-gene signature based on EMT in the prognosis, immunity, and treatment of lung squamous cell carcinoma

Epithelial-mesenchymal transition (EMT), a biological process through which epithelial cells transform into mesenchymal cells, contributes to tumor progression and metastasis. However, a comprehensive analysis of the role of EMT-related genes in Lung squamous cell carcinoma (LUSC) is still lacking. In this study, data were downloaded from available databases, including The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The association between differentially expressed EMT-related genes (EMT-RDGs) and LUSC prognosis, drug sensitivity, mutation, and immunity was analyzed using bioinformatics methods. In the results, Lasso and univariate Cox regression analyses identified four EMT-RDGs that were differentially expressed, and used to establish a prognostic model capable of distinguishing between high- and low-risk groups. Then, prognostic factors were identified by multivariate Cox regression analysis and used to construct a nomogram. The high-risk group had a significantly poorer prognosis than the low-risk group. The tumor immune environment was significantly different between the two groups, with the low-risk group exhibiting a better response to immunotherapy. In addition, the half-maximal inhibitory concentration prediction indicating that the constructed model could effectively predict sensitivity to chemotherapy. This study provides new reference for further exploration of new clinical therapeutic strategies for LUSC.

Target-independent hybridization chain reaction-fluorescence resonance energy transfer for sensitive assay of ctDNA based on Cas12a

Circulating tumor DNA (ctDNA) is a noninvasive biomarker which offer valuable information for cancer diagnosis and prognosis. In this study, a target-independent fluorescent signal system, Hybridization chain reaction-Fluorescence resonance energy transfer (HCR-FRET) system, is designed and optimized. Combined with CRISPR/Cas12a system, a fluorescent biosensing protocol was developed for sensing assay of T790 M. When the target is absent, the initiator remains intact, opens the fuel hairpins and triggers the following HCR-FRET. At presence of the target, the Cas12a/crRNA binary complex specifically recognizes the target, and the Cas12a trans-cleavage activity is activated. As a result, the initiator is cleaved and subsequent HCR responses and FRET processes are attenuated. This method showed detection range from 1 pM to 400 pM with a detection limit of 316 fM. The target independent property of the HCR-FRET system endows this protocol a promising potential to transplant to the assay of other DNA target in parallel.

Prophylactic cranial irradiation-related lymphopenia affects survival in patients with limited-stage small cell lung cancer

Background

The study aimed to identify the relations of the absolute lymphocyte count (ALC) nadir during prophylactic cranial irradiation (PCI) and patient outcomes in limited-stage small cell lung cancer (LS-SCLC).

Methods

We analyzed 268 L S-SCLC patients who underwent PCI from 2012 to 2019. ALC values were collected prior, during, and 3 months post PCI. Kaplan-Meier and Cox regression analyses were performed to assess the relation of ALC to patient prognosis. Two nomograms were developed on the basis of clinical variables for survival prediction.

Results

Compared with the ALC before PCI (1.13 × 10⁹ cells/L), the ALC nadir during PCI was significantly reduced by 0.68 × 10⁹ cells/L (P < 0.001) and raised to 1.02 × 10⁹ cells/L 3 months post PCI. Patients with a low ALC nadir during PCI (<0.68 × 10⁹ cells/L) had inferior progression free survival (PFS) (median PFS: 17.2 m vs. 43.7 m, P = 0.019) and overall survival (OS) (median OS: 29.0 m vs 39.1 m, P = 0.012). Multivariate Cox analysis revealed that age, smoking history, clinical stage, and ALC nadir were independent OS (P = 0.006, P = 0.005, P < 0.001 and P = 0.027, respectively), as well as independent PFS predictors (P = 0.032, P = 0.012, P = 0.012 and P = 0.018, respectively). After internal cross-validation, the corrected concordance indices of the predictive nomograms for PFS and OS were 0.637 and 0.663, respectively.

Conclusion

LS-SCLC patients with a low ALC nadir during PCI likely have worse survival outcomes. Dynamic evaluation of the ALC during PCI is recommended for LS-SCLC patients.

Comparative expression analysis of immune-related markers in surgically resected lung neuroendocrine neoplasms

BACKGROUND

Although immunotherapy has led to a paradigm shift in the treatment of lung cancer, the therapeutic approaches for lung neuroendocrine neoplasms (LNENs) are still limited. Our aim was to explore the immunological landscape and the expression of immune checkpoint markers in LNENs.

METHODS

Surgically removed tumor samples of 26 atypical carcinoid (AC), 30 large cell neuroendocrine carcinoma (LCNEC) and 29 small cell lung cancer (SCLC) patients were included. The immune phenotype of each tumor type was assessed by using a panel of 15 immune-related markers. As these markers are potentially expressed by immune cells and/or tumor cells, they might serve as putative targets for immunotherapy. Expression patterns were measured by immunohistochemistry and correlated with clinicopathological parameters and prognosis.

RESULTS

Unsupervised hierarchical clustering revealed distinct immunologic profiles across tumor types. Specifically, AC tumors were characterized by high tumor cell CD40 expression and low levels of immune infiltrates whereas SCLC samples had a high CD47 and Inducible T Cell Costimulator (ICOS) expression in tumor cells and immune cells, respectively. High CD70 and CD137 expression by tumor cells as well as elevated expression of CD27, Lymphocyte Activation Gene 3 (LAG3), and CD40 by immune cells were characteristic for LCNEC samples. Overall, SCLC and LCNEC tumors had a more immunogenic phenotype than AC samples. High tumor cell CD47 and CD40 expressions were associated with impaired and improved survival outcomes, respectively.

CONCLUSIONS

By providing insights into the widely divergent immunologic profiles of LNENs, our results might serve as a basis for the development of novel immunotherapy-related approaches in these devastating malignancies.

Artificial intelligence-quantified tumour-lymphocyte spatial interaction predicts disease-free survival in resected lung adenocarcinoma: A graph-based, multicentre study

BACKGROUND AND OBJECTIVE

A high degree of lymphocyte infiltration is related to superior outcomes amongst patients with lung adenocarcinoma. Recent evidence indicates that the spatial interactions between tumours and lymphocytes also influence the anti-tumour immune responses, but the spatial analysis at the cellular level remains insufficient.

METHODS

We proposed an artificial intelligence-quantified Tumour-Lymphocyte Spatial Interaction score (TLSI-score) by calculating the ratio between the number of spatial adjacent tumour-lymphocyte and the number of tumour cells based on topology cell graph constructed using H&E-stained whole-slide images. The association of TLSI-score with disease-free survival (DFS) was explored in 529 patients with lung adenocarcinoma across three independent cohorts (D1, 275; V1, 139; V2, 115).

RESULTS

After adjusting for pTNM stage and other clinicopathologic risk factors, a higher TLSI-score was independently associated with longer DFS than a low TLSI-score in the three cohorts [D1, adjusted hazard ratio (HR), 0.674; 95% confidence interval (CI) 0.463-0.983; p = 0.040; V1, adjusted HR, 0.408; 95% CI 0.223-0.746; p = 0.004; V2, adjusted HR, 0.294; 95% CI 0.130-0.666; p = 0.003]. By integrating the TLSI-score with clinicopathologic risk factors, the integrated model (full model) improves the prediction of DFS in three independent cohorts (C-index, D1, 0.716 vs. 0.701; V1, 0.666 vs. 0.645; V2, 0.708 vs. 0.662) CONCLUSIONS: TLSI-score shows the second highest relative contribution to the prognostic prediction model, next to the pTNM stage. TLSI-score can assist in the characterising of tumour microenvironment and is expected to promote individualized treatment and follow-up decision-making in clinical practice.

A pilot study on pyroptosis related genes in peripheral blood mononuclear cells of non-small cell lung cancer patients

OBJECTIVE

To investigate the GSDMD, CASP1, CASP4 and CASP5 expression in peripheral blood mononuclear cells of non-small cell lung cancer patients and analyze their clinical significance.

METHODS

71 non-small cell lung cancer patients were selected as the study group and 50 healthy individuals as the control group. The GSDMD, CASP1, CASP4 and CASP5 expression in peripheral blood mononuclear cells of the two groups were detected by real-time fluorescence quantitative PCR. The GSDMD, CASP1, CASP4, CASP5 expression and their relationship with the clinical characteristics of the patients were analyzed.

RESULTS

Compared with the control group, the GSDMD, CASP4 and CASP5 expression in PBMCs of lung cancer patients was significantly higher(P < 0.05). Lymph node metastasis had significant difference with the CASP4 and GSDMD expression (P < 0.05); tumor volume had significant difference with CASP1 and CASP5 expression (P < 0.05). The areas under predictive ROC curve of the GSDMD, CASP1, CASP4, and CASP5 mRNA expression were 0.629(P < 0.05), 0.574(p > 0.05), 0.701(P < 0.05) and 0.628(P < 0.05), the sensitivity values were 84.5%, 67.6% 43.7%, and 84.3%;the specificity values were 42%, 52%, 84% and 64%, respectively.

CONCLUSION

GSDMD, CASP1, CASP4 and CASP5 gene expression are highly increased in PBMCs of non-small cell lung cancer patients and their expression are closely related to the clinical characteristics of patients. The early enhanced pyroptosis-related gene expression may be potential molecular markers for early diagnosis of non-small cell lung cancer.