Tumor Immune Microenvironment and Immunotherapy in Non-Small Cell Lung Cancer: Update and New Challenges

Pan-cancer analysis of CDKN2A alterations identifies a subset of gastric cancer with a cold tumor immune microenvironment

BACKGROUND

Although CDKN2A alteration has been explored as a favorable factor for tumorigenesis in pan-cancers, the association between CDKN2A point mutation (MUT) and intragenic deletion (DEL) and response to immune checkpoint inhibitors (ICIs) is still disputed. This study aims to determine the associations of CDKN2A MUT and DEL with overall survival (OS) and response to immune checkpoint inhibitors treatment (ICIs) among pan-cancers and the clinical features of CDKN2A-altered gastric cancer.

METHODS

This study included 45,000 tumor patients that underwent tumor sequencing across 33 cancer types from four cohorts, the MSK-MetTropism, MSK-IMPACT, OrigiMed2020 and TCGA cohorts. Clinical outcomes and genomic factors associated with response to ICIs, including tumor mutational burden, copy number alteration, neoantigen load, microsatellite instability, tumor immune microenvironment and immune-related gene signatures, were collected in pan-cancer. Clinicopathologic features and outcomes were assessed in gastric cancer. Patients were grouped based on the presence of CDKN2A wild type (WT), CDKN2A MUT, CDKN2A DEL and CDKN2A other alteration (ALT).

RESULTS

Our research showed that CDKN2A-MUT patients had shorter survival times than CDKN2A-WT patients in the MSK MetTropism and TCGA cohorts, but longer OS in the MSK-IMPACT cohort with ICIs treatment, particularly in patients having metastatic disease. Similar results were observed among pan-cancer patients with CDKN2A DEL and other ALT. Notably, CDKN2A ALT frequency was positively related to tumor-specific objective response rates to ICIs in MSK MetTropism and OrigiMed 2020. Additionally, individuals with esophageal carcinoma or stomach adenocarcinoma who had CDKN2A MUT had poorer OS than patients from the MSK-IMPACT group, but not those with adenocarcinoma. We also found reduced levels of activated NK cells, T cells CD8 and M2 macrophages in tumor tissue from CDKN2A-MUT or DEL pan-cancer patients compared to CDKN2A-WT patients in TCGA cohort. Gastric cancer scRNA-seq data also showed that CDKN2A-ALT cancer contained less CD8 T cells but more exhausted T cells than CDKN2A-WT cancer. A crucial finding of the pathway analysis was the inhibition of three immune-related pathways in the CDKN2A ALT gastric cancer patients, including the interferon alpha response, inflammatory response, and interferon gamma response.

CONCLUSIONS

This study illustrates the CDKN2A MUT and DEL were associated with a poor outcome across cancers. CDKN2A ALT, on the other hand, have the potential to be used as a biomarker for choosing patients for ICI treatment, notably in esophageal carcinoma and stomach adenocarcinoma.

Biological clock regulation by the PER gene family: a new perspective on tumor development

The Period (PER) gene family is one of the core components of the circadian clock, with substantial correlations between the PER genes and cancers identified in extensive researches. Abnormal mutations in PER genes can influence cell function, metabolic activity, immunity, and therapy responses, thereby promoting the initiation and development of cancers. This ultimately results in unequal cancers progression and prognosis in patients. This leads to variable cancer progression and prognosis among patients. In-depth studies on the interactions between the PER genes and cancers can reveal novel strategies for cancer detection and treatment. In this review, we aim to provide a comprehensive overview of the latest research on the role of the PER gene family in cancer.

An endothelial-related prognostic index for bladder cancer patients

BACKGROUND

Within the tumor microenvironment, endothelial cells hold substantial sway over bladder cancer (BC) prognosis. Herein, we aim to elucidate the impact of endothelial cells on BC patient outcomes by employing an integration of single-cell and bulk RNA sequencing data.

METHODS

All data utilized in this study were procured from online databases. R version 3.6.3 and relevant packages were harnessed for the development and validation of an endothelial-associated prognostic index (EPI).

RESULTS

EPI was formulated, incorporating six genes (CYTL1, FAM43A, GSN, HSPG2, RBP7, and SLC2A3). EPI demonstrated significant prognostic value in both The Cancer Genome Atlas (TCGA) and externally validated dataset. Functional results revealed a profound association between EPI and endothelial cell functionality, as well as immune-related processes. Our findings suggest that patients with low-risk EPI scores are more likely to respond positively to immunotherapy, as indicated by immune checkpoint activity, immune infiltration, tumor mutational burden, stemness index, TIDE, and IMvigor210 analyses. Conversely, individuals with high-risk EPI scores exhibited heightened sensitivity to cisplatin, docetaxel, and gemcitabine treatment regimens.

CONCLUSION

We have effectively discerned pivotal genes from the endothelial cell perspective and constructed an EPI for BC patients, thereby offering promising prospects for precision medicine.

Identification of lung adenocarcinoma subtypes and a prognostic signature based on activity changes of the hallmark and immunologic gene sets

Background

Lung adenocarcinoma (LUAD) has a complex tumor heterogeneity. Our research attempts to clearness LUAD subtypes and build a reliable prognostic signature according to the activity changes of the hallmark and immunologic gene sets.

Methods

According to The Cancer Genome Atlas (TCGA) - LUAD dataset, changes in marker and immune gene activity were analyzed, followed by identification of prognosis-related differential gene sets (DGSs) and their related LUAD subtypes. Survival analysis, correlation with clinical characteristics, and immune microenvironment assessment for subtypes were performed. Moreover, the differentially expressed genes (DEGs) between different subtypes were identified, followed by the construction of a prognostic risk score (RS) model and nomogram model. The tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) of different risk groups were compared.

Results

Two LUAD subtypes were determined according to the activity changes of the hallmark and immunologic gene sets. Cluster 2 had worse prognosis, more advanced tumor and clinical stages than cluster 1. Moreover, a prognostic RS signature was established using two LUAD subtype-related DEGs, which could stratify patients at different risk levels. Nomogram model incorporated RS and clinical stage exerted good prognostic performance in LUAD patients. A shorter survival time and higher TMB were observed in the high-risk patients.

Conclusions

Our findings revealed that our constructed prognostic signature could exactly predict the survival status of LUAD cases, which was helpful in predicting the prognosis and guiding personalized therapeutic strategies for LUAD.

MYC Oncogene: A Druggable Target for Treating Cancers with Natural Products

Various diseases, including cancers, age-associated disorders, and acute liver failure, have been linked to the oncogene, MYC. Animal testing and clinical trials have shown that sustained tumor volume reduction can be achieved when MYC is inactivated, and different combinations of therapeutic agents including MYC inhibitors are currently being developed. In this review, we first provide a summary of the multiple biological functions of the MYC oncoprotein in cancer treatment, highlighting that the equilibrium points of the MYC/MAX, MIZ1/MYC/MAX, and MAD (MNT)/MAX complexes have further potential in cancer treatment that could be used to restrain MYC oncogene expression and its functions in tumorigenesis. We also discuss the multifunctional capacity of MYC in various cellular cancer processes, including its influences on immune response, metabolism, cell cycle, apoptosis, autophagy, pyroptosis, metastasis, angiogenesis, multidrug resistance, and intestinal flora. Moreover, we summarize the MYC therapy patent landscape and emphasize the potential of MYC as a druggable target, using herbal medicine modulators. Finally, we describe pending challenges and future perspectives in biomedical research, involving the development of therapeutic approaches to modulate MYC or its targeted genes. Patients with cancers driven by MYC signaling may benefit from therapies targeting these pathways, which could delay cancerous growth and recover antitumor immune responses.

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.

Assessing the causal relationship between 731 immunophenotypes and the risk of lung cancer: a bidirectional mendelian randomization study

BACKGROUND

Previous studies have observed a link between immunophenotypes and lung cancer, both of which are closely associated with genetic factors. However, the causal relationship between them remains unclear.

METHODS

Bidirectional Mendelian randomization (MR) was performed on publicly available genome-wide association study (GWAS) summary statistics to analyze the causal relationships between 731 immunophenotypes and lung cancer. Sensitivity analyses were conducted to verify the robustness, heterogeneity, and potential horizontal pleiotropy of our findings.

RESULTS

Following Bonferroni adjustment, CD14- CD16+ monocyte (OR = 0.930, 95%CI 0.900-0.960, P = 8.648 × 10- 6, PBonferroni = 0.006) and CD27 on CD24+ CD27+ B cells (OR = 1.036, 95%CI 1.020-1.053, P = 1.595 × 10 - 5, PBonferroni = 0.012) were identified as having a causal role in lung cancer via the inverse variance weighted (IVW) method. At a more relaxed threshold, CD27 on IgD+ CD24+ B cell (OR = 1.035, 95%CI 1.017-1.053, P = 8.666 × 10- 5, PBonferroni = 0.063) and CD27 on switched memory B cell (OR = 1.037, 95%CI 1.018-1.056, P = 1.154 × 10- 4, PBonferroni = 0.084) were further identified. No statistically significant effects of lung cancer on immunophenotypes were found.

CONCLUSIONS

The elevated level of CD14- CD16+ monocytes was a protective factor against lung cancer. Conversely, CD27 on CD24+ CD27+ B cell was a risk factor. CD27 on class-switched memory B cells and IgD+ CD24+ B cells were potential risk factors for lung cancer. This research enhanced our comprehension of the interplay between immune responses and lung cancer risk. Additionally, these findings offer valuable perspectives for the development of immunologically oriented therapeutic strategies.

Dysregulated ANLN reveals immune cell landscape and promotes carcinogenesis by regulating the PI3K/Akt/mTOR pathway in clear cell renal cell carcinoma

Background

Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).

Methods

We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.

Results

Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.

Conclusions

These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

Identification of neutrophil-related genes and development of a prognostic model for cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is a prevalent gastrointestinal tumor with limited effective early diagnostic methods. The role of neutrophils in the context of cholangiocarcinoma remains largely unexplored.

METHODS

A comprehensive analysis was performed on a cohort of cholangiocarcinoma samples (TCGA-CHOL) from the TCGA database to investigate the relationship between cholangiocarcinoma and neutrophils. Methodologies included single-sample gene set enrichment analysis (ssGSEA), differential expression analysis, weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA).

RESULTS

The study identified a significant decrease of neutrophils in cholangiocarcinoma via ssGSEA. WGCNA and differential expression analysis led to the identification of a neutrophil-related gene module comprised of 1059 genes. Cluster 1, showing a higher proportion of neutrophils, was linked to better survival outcomes. GSEA disclosed downregulation of complement, inflammatory response and interferon response pathways in Cluster 2, hinting at possible cholangiocarcinoma development triggers. A notable upregulation of PD1, PD-L1 and CTLA4 was observed in Cluster 1, suggesting potential benefits from immunotherapy. A prognostic model was developed based on clinical data and expression levels of three prognostic genes (SOWAHD, TNFAIP8 and EBF3) showing satisfactory discrimination, calibration and clinical benefits. An overexpression of TNFAIP8 in cholangiocarcinoma cells was found, with its knockdown significantly inhibiting cell proliferation and migration.

CONCLUSIONS

This study elucidates a neutrophil-related gene module and prognostic genes, offering insights into the role of neutrophils in cholangiocarcinoma development and progression. It also introduces a clinical prediction model for enhanced prognosis assessment. These findings may lay the groundwork for the development of innovative therapeutic strategies in cholangiocarcinoma treatment.

Development of an ubiquitin-proteasome system signature for predicting prognosis and providing therapeutic guidance for patients with triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a pathological subtype with a high mortality, and the development of inhibitors in the ubiquitin-proteasome system (UPS) component could be a novel therapeutic tool.

METHODS

Triple-negative breast cancer data were obtained from The Cancer Genome Atlas (TCGA), and subtype analysis was performed by consistent clustering analysis to identify molecular subtypes of TNBC according to UPS characteristics. Differential analysis, COX and least absolute shrinkage and selection operator (LASSO) COX regression analyses were performed to select genes associated with overall survival in TNBC. The final prognostic model (UPS score) was determined using the LASSO COX model. The model performance was assessed using receiver operating characteristic (ROC) curves and survival curves. In addition, the results of the UPS score on analyzing the abundance of immune cell infiltration and immunotherapy were explored. Finally, we developed a nomogram for TNBC survival prediction.

RESULTS

Two UPS subtypes (UPSMS1 and UPSMS2) showing significant survival differences were classified. COX regression analysis on differentially expressed genes in UPSMS1 and UPSMS2 filtered five genes that affected overall survival. Based on the regression coefficients and expression data of the five genes, we built a prognostic assessment system (UPS score). The UPS score showed consistent prognostic and therapeutic guidance values. Finally, the ROC curve of the nomogram and UPS score showed the highest predictive efficacy compared with traditional clinical prognostic indicators.

CONCLUSION

The UPS score represented a promising prognostic tool to predict overall survival and immune status and guide personalized treatment selection in TNBC patients, and this study may provide a more practical alternative for clinical monitoring and management of TNBC.

Amino acids and their roles in tumor immunotherapy of breast cancer

Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.

Machine learning reveals PANoptosis as a potential reporter and prognostic revealer of tumour microenvironment in lung adenocarcinoma

Lung adenocarcinoma (LUAD), a prominent lung cancer subtype, has an underexplored relationship with PANoptosis, a recently discovered mode of tumour cell death. This study incorporated iron death, copper death, scorch death, necrotizing apoptosis and bisulfide death into a pan-death gene set (PANoptosis) and conducted single-cell analysis of scRNA-seq data from 11 LUAD samples. Differentially expressed genes were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed. Univariate COX regression and least absolute shrinkage and selection operator (LASSO) regression were used to screen PANoptosis key genes for constructing an LUAD risk model. The model's prognostic performance was evaluated using survival curves, risk scores and validation in the Gene Expression Omnibus database. The study also explored the correlation between risk scores, tumour biological function, immunotherapy, drug sensitivity and immune infiltration. The SMS gene in the PANoptosis model was silenced in two LUAD cell lines for cellular validation. Single-cell analysis revealed eight major cell types and several PANoptosis genes significantly associated with LUAD survival. The risk model demonstrated strong prognostic performance and association with immune infiltration, suggesting PANoptosis involvement in LUAD tumour immunity. Cellular validation further supported these findings. The PANoptosis key risk genes are believed to be closely related to the tumour microenvironment and immune regulation of LUAD, potentially providing valuable insights for early diagnosis and clinical treatment, and broader applications in other tumours and complex diseases.

Mapping the landscape of immunonutrition and cancer research: a comprehensive bibliometric analysis on behalf of NutriOnc Research Group

The ongoing global health challenge of cancer is driving the pursuit of innovative avenues for prevention, treatment, and enhanced outcomes. The convergence of nutrition and immune modulation, known as immunonutrition, is ready to act as a catalyst for transformative change in cancer research and therapy. Our study employs a bibliometric analysis to uncover the evolving trends within immunonutrition and cancer research across the past 25 years. Bibliometric data, including authors, journals, affiliations, and countries, were analyzed using the Bibliometrix R package. Clustering algorithms were applied to keywords to identify thematic areas and their evolution. A total of 489 documents were analyzed, showing an annual growth rate of 8.7%, with a collaboration index of 5.41, highlighting comprehensive multidisciplinary involvement within this landscape. Core authors demonstrated sustained productivity, while occasional authors indicated widespread interest. The Medical University of Warsaw led in institutional contributions. Country-wise, Italy, France, and the USA emerged as forerunners in fostering research productivity. Key journals like 'Clinical Nutrition' served as beacons, emphasizing the multidimensional nature of this topic. The analysis highlighted growing research output and several collaborations, indicating the importance of immunoenriched nutrition in cancer treatment. The interplay of core authors and diversified engagement harmoniously accentuates the cross-disciplinary nature of this burgeoning field. International collaboration facilitated knowledge exchange. Prominent documents shaped the field, emphasizing the significance of nutritional interventions. Thematic clusters revealed varied focuses, including pharmaconutrients, surgical approaches, inflammation, and specific cancers. The expanding research output suggests further development, particularly in exploring immunoenriched nutrition's impact on cancer types and patient populations. The multidisciplinary nature and international collaborations enhance the field's progress. Gaps in research underscore the need for original studies and personalized approaches. This study guides future research, informing evidence-based nutritional interventions and advancing cancer care practices.

Unveiling clinical significance and tumor immune landscape of CXCL12 in bladder cancer: Insights from multiple omics analysis

Objective

The interplay between chemokine C-X-C motif ligand 12 (CXCL12) and its specific receptors is known to trigger various signaling pathways, contributing to tumor proliferation and metastasis. Consequently, targeting this signaling axis has emerged as a potential strategy in cancer therapy. However, the precise role of CXCL12 in clinical therapy, especially in immunotherapy for bladder cancer (BCa), remains poorly elucidated.

Methods

We gathered multiple omics data from public databases to unveil the clinical relevance and tumor immune landscape associated with CXCL12 in BCa patients. Univariate and multivariate Cox regression analyses were employed to assess the independent prognostic significance of CXCL12 expression and formulate a nomogram. The expression of CXCL12 in BCa cell lines and clinical tissue samples was validated using enzyme-linked immunosorbent assays (ELISA) and immunohistochemistry (IHC).

Results

While transcriptional expression of CXCL12 exhibited a decrease in nearly all tumor tissues, CXCL12 methylation expression was notably increased in BCa tissues. Single-cell RNA analysis highlighted tissue stem cells and endothelial cells as the primary sources expressing CXCL12. Abnormal CXCL12 expression, based on transcriptional and methylation levels, correlated with various clinical characteristics in BCa patients. Functional analysis indicated enrichment of CXCL12 and its co-expression genes in immune regulation and cell adhesion. The immune landscape analysis unveiled a significant association between CXCL12 expression and M2 macrophages (CD163+ cells) in BCa tissues. Notably, CXCL12 expression emerged as a potential predictor of immunotherapy response and chemotherapy drug sensitivity in BCa patients.

Conclusions

Taken together, these findings suggest aberrant production of CXCL12 in BCa tissues, potentially influencing the treatment responses of affected individuals.

CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

Finding biomarkers for immunotherapy is an urgent issue in cancer treatment. Cellular retinoic acid-binding protein 2 (CRABP2) is a controversial factor in the occurrence and development of human tumors. However, there is limited research on the relationship between CRABP2 and immunotherapy response. This study found that negative correlations of CRABP2 and immune checkpoint markers (PD-1, PD-L1, and CTLA-4) were observed in breast invasive carcinoma (BRCA), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD) and testicular germ cell tumors (TGCT). In particular, in SKCM patients who were treated with PD-1 inhibitors, high levels of CRABP2 predicted poor prognosis. Additionally, CRABP2 expression was elevated in cancer-associated fibroblasts (CAFs) at the single-cell level. The expression of CRABP2 was positively correlated with markers of CAFs, such as MFAP5, PDPN, ITGA11, PDGFRα/β and THY1 in SKCM. To validate the tumor-promoting effect of CRABP2 in vivo, SKCM xenograft mice models with CRABP2 overexpression have been constructed. These models showed an increase in tumor weight and volume. Enrichment analysis indicated that CRABP2 may be involved in immune-related pathways of SKCM, such as extracellular matrix (ECM) receptor interaction and epithelial-mesenchymal transition (EMT). The study suggests that CRABP2 may regulate immunotherapy in SKCM patients by influencing infiltration of CAFs. In conclusion, this study provides new insights into the role of CRABP2 in immunotherapy response. The findings suggest that CRABP2 may be a promising biomarker for PD-1 inhibitors in SKCM patients. Further research is needed to confirm these findings and to explore the clinical implications of CRABP2 in immunotherapy.

Comprehensive analysis of mitophagy-related genes in NSCLC diagnosis and immune scenery: based on bulk and single-cell RNA sequencing data

Lung cancer is the main cause of cancer-related deaths, and non-small cell lung cancer (NSCLC) is the most common type. Understanding the potential mechanisms, prognosis, and treatment aspects of NSCLC is essential. This study systematically analyzed the correlation between mitophagy and NSCLC. Six mitophagy-related feature genes (SRC, UBB, PINK1, FUNDC1, MAP1LC3B, and CSNK2A1) were selected through machine learning and used to construct a diagnostic model for NSCLC. These feature genes are closely associated with the occurrence and development of NSCLC. Additionally, NSCLC was divided into two subtypes using unsupervised consensus clustering, and their differences in clinical characteristics, immune infiltration, and immunotherapy were systematically analyzed. Furthermore, the interaction between mitophagy-related genes (MRGs) and immune cells was analyzed using single-cell sequencing data. The findings of this study will contribute to the development of potential diagnostic biomarkers for NSCLC and the advancement of personalized treatment strategies.

Supramolecular host-guest nanosystems for overcoming cancer drug resistance

Cancer drug resistance has become one of the main challenges for the failure of chemotherapy, greatly limiting the selection and use of anticancer drugs and dashing the hopes of cancer patients. The emergence of supramolecular host-guest nanosystems has brought the field of supramolecular chemistry into the nanoworld, providing a potential solution to this challenge. Compared with conventional chemotherapeutic platforms, supramolecular host-guest nanosystems can reverse cancer drug resistance by increasing drug uptake, reducing drug efflux, activating drugs, and inhibiting DNA repair. Herein, we summarize the research progress of supramolecular host-guest nanosystems for overcoming cancer drug resistance and discuss the future research direction in this field. It is hoped that this review will provide more positive references for overcoming cancer drug resistance and promoting the development of supramolecular host-guest nanosystems.

Prognostic factors and survival prediction of resected non-small cell lung cancer with ipsilateral pulmonary metastases: a study based on the Surveillance, Epidemiology, and End Results (SEER) database

BACKGROUND

Prognostic factors and survival outcomes of non-small cell lung cancer (NSCLC) with Ipsilateral pulmonary metastasis (IPM) are not well-defined. Thus, this study intended to identify the prognostic factors for these patients and construct a predictive nomogram model.

METHODS

One thousand, seven hundred thirty-two patients with IPM identified between 2000 to 2019 were from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified using multivariate Cox regression analyses. Nomograms were constructed to predict the overall survival (OS), C-index, the area under the curve (AUC), and the calibration curve to determine the predictive accuracy and discrimination; the decision curve analysis was used to confirm the clinical utility.

RESULTS

Patients were randomly divided into training (n = 1213) and validation (n = 519) cohorts. In the training cohort, the multivariable analysis demonstrated that age, sex, primary tumor size, N status, number of regional lymph nodes removed, tumor grade, and chemotherapy were independent prognostic factors for IPM. We constructed a 1-year, 3-year, and 5-year OS prediction nomogram model using independent prognostic factors. The C-index of this model for OS prediction was 0.714 (95% confidence interval [CI], 0.692 to 0.773) in the training cohort and 0.695 (95% CI, 0.660 to 0.730) in the validation cohort. Based on the AUC of the receiver operating characteristic analysis, calibration plots, and decision curve analysis, we concluded that the prognosis model of IPM exhibited excellent performance. Patients with total nomogram points greater than 96 were considered high-risk.

CONCLUSION

We constructed and internally validated a nomogram to predict 1-year, 3-year, and 5-year OS for NSCLC patients with IPM according to independent prognostic factors. This nomogram demonstrated good calibration, discrimination, clinical utility, and practical decision-making effects for the prognosis of NSCLC patients with IPM.

An online clinical model and risk stratification system to predict progression-free survival for advanced non-small-cell lung cancer patients treated with PD-(L)1 inhibitor

Background

Our study aimed to build a risk stratification system predicting the progression-free survival (PFS) to classify patients into diverse prognostic subgroups for advanced non-small-cell lung cancer patients treated with PD-(L)1 inhibitor.

Methods

404 patients from our center were enrolled in this study and 70% patients (n = 282) were randomly assigned into the training cohort and other 30% patients (n = 122) into the validation cohort. A testing cohort contained 81 patients from other centers were used to assess the generalizability of model. Cox regression analyses were used to identify the most significant clinical parameters. The model's performance was assessed by using concordance index (C-index), calibration curves, Decision Curve Analyses (DCAs), net reclassification improvement (NRI), integrated discrimination improvement (IDI) analyses, and survival curve.

Results

Five clinical parameters were identified as the most significant predictors by using cox regression. We then integrated them into a Nomogram to Evaluate the relative PFS of ICIs Treatment (NEPIT). The C-index of NEPIT in the training cohort, the validation cohort and testing cohort was 0.789 (95%CI: 0.750-0.828), 0.745 (95%CI: 0.706-0.784), and 0.766 (95%CI: 0.744-0.788), respectively. The calibration curves presented a good congruence between the predictions and actual observations. The Decision Curve Analyses (DCAs) reflected positive net benefits can be obtained for NEPIT. The results from NRI and IDI analyses showed that the NEPIT could improve predictive power of TPS. In addition, the further constructed risk stratification system could effectively categorize patients into different risk subgroups.

Conclusion

The tools developed in this study would have value in guiding the optimal patient selection for precision care.

Relationship between plasma circulating cell-free DNA concentration and treatment outcomes including prognosis in patients with advanced non-small cell lung cancer

BACKGROUND

Some research found that elevated plasma cell-free DNA (cfDNA) concentrations and poor prognosis are associated in non-small cell lung cancer (NSCLC). However, more studies need to be carried out to verify this conclusion. Therefore, this study investigated the relationship between cfDNA concentration and treatment outcomes including prognosis in patients with advanced NSCLC.

METHODS

We retrospectively collected medical records and cfDNA data from 160 patients with advanced NSCLC. Progression-free survival (PFS) were calculated using the Kaplan-Meier method and were compared between groups using the log rank test. Cox regression analysis was used for estimating the independent predictors of PFS. And we used logistic regression to evaluate the relationship between baseline biomarkers and efficacy. In our study, BT1 cfDNA, BT2 cfDNA, and BT3 cfDNA were defined as cfDNA concentration before the first treatment (baseline cfDNA concentration), cfDNA concentration before the second treatment, and cfDNA concentration before the third treatment, respectively.

RESULTS

Patients with low cfDNA (BT1 cfDNA < 15 (ng/mL)) were reported a significantly prolonged median progression-free survival (mPFS) compared with patients with patients with high cfDNA (BT1 cfDNA ≥ 15(ng/mL)) (mPFS: 14.6 vs. 8.3 months, P = 0.002), as well as patients with neutrophil/lymphocyte ratio (NLR)<2.98 (mPFS: 13.1 vs. 7.9 months, P = 0.023). In addition, Cox proportional hazards regression analysis identified independent indicators associated with PFS including BT1 cfDNA ≥ 15 (ng/mL), NLR ≥ 2.98 and extrapulmonary metastasis. The best cut-off value for BT3 cfDNA for predicting disease progression is 41.46 (ng/mL) (Area Under the Curve (AUC): 0.652, 95%CI: 0.516-0.788), achieving 90.7% sensitivity and 37.5% specificity for the prediction of disease progression. BT3 cfDNA (OR = 6.08, 95% CI: 1.94-19.57, P = 0.002) was an independent factor for disease progression in patients with advanced NSCLC.

CONCLUSIONS

BT1 cfDNA may be a biomarker to assess the prognosis of advanced NSCLC. Patients with advanced NSCLC with lower cfDNA and NLR before treatment had a better prognosis. Increased BT3 cfDNA concentration was an independent factor of disease progression in advanced NSCLC patients. These findings may assist in identifying high-risk patients and guiding treatment strategies.

Adhesion-regulating molecule 1 (ADRM1) can be a potential biomarker and target for bladder cancer

Adhesion-regulating molecule 1 (ADRM1) has been implicated in tumor development, yet its specific role in bladder cancer (BC) remains undefined. This study aimed to elucidate the function of ADRM1 in BC through a combination of bioinformatics analysis and immunohistochemical analysis (IHC). Utilizing R version 3.6.3 and relevant packages, we analyzed online database data. Validation was conducted through IHC data, approved by the Institutional Ethics Committee (Approval No. K20220830). In both paired and unpaired comparisons, ADRM1 expression was significantly elevated in BC tissues compared to adjacent tissues, as evidenced by the results of TCGA dataset and IHC data. Patients with high ADRM1 expression had statistically worse overall survival than those with low ADRM1 expression in TCGA dataset, GSE32548 dataset, GSE32894 dataset, and IHC data. Functional analysis unveiled enrichment in immune-related pathways, and a robust positive correlation emerged between ADRM1 expression and pivotal immune checkpoints, including CD274, PDCD1, and PDCD1LG2. In tumor microenvironment, samples with the high ADRM1 expression contained statistical higher proportion of CD8 + T cells and Macrophage infiltration. Meanwhile, these high ADRM1-expressing samples displayed elevated tumor mutation burden scores and stemness indices, implying potential benefits from immunotherapy. Patients with low ADRM1 expression were sensitive to cisplatin, docetaxel, vinblastine, mitomycin C, and methotrexate. According to the findings from bioinformatics and IHC analyses, ADRM1 demonstrates prognostic significance for BC patients and holds predictive potential for both immunotherapy and chemotherapy responses. This underscores its role as a biomarker and therapeutic target in BC.

Identification and validation of a novel anoikis-related signature for predicting prognosis and immune landscape in ovarian serous cystadenocarcinoma

BACKGROUND

Ovarian serous cystadenocarcinoma (OSC) is the most prevalent histological subtype of ovarian cancer (OV) and presents a serious threat to women's health. Anoikis is an essential component of metastasis, and tumor cells can get beyond it to become viable. The impact of anoikis on OSC, however, has only been the topic of a few studies.

METHODS

The mRNA sequencing and clinical information of OSC came from The Cancer Genome Atlas Target Genotype-Tissue Expression (TCGA TARGET GTEx) dataset. Anoikis-related genes (ARGs) were collected by Harmonizome and GeneCards websites. Centered on these ARGs, we used unsupervised consensus clustering to explore potential tumor typing and filtered hub ARGs to create a model of predictive signature for OSC patients. Furthermore, we presented clinical specialists with a novel nomogram based on ARGs, revealing the underlying clinical relevance of this signature. Finally, we explored the immune microenvironment among various risk groups.

RESULTS

We identified 24 ARGs associated with the prognosis of OSC and classified OSC patients into three subtypes, and the subtype with the best prognosis was more enriched in immune-related pathways. Seven ARGs (ARHGEF7, NOTCH4, CASP2, SKP2, PAK4, LCK, CCDC80) were chosen to establish a risk model and a nomogram that can provide practical clinical decision support. Risk scores were found to be an independent and significant prognostic factor in OSC patients. The CIBERSORTx result revealed an inflammatory microenvironment is different for risk groups, and the proportion of immune infiltrates of Macrophages M1 is negatively correlated with risk score (rs = -0.21, P < 0.05). Ultimately, quantitative reverse transcription polymerase chain reaction (RT-PCR) was utilized to validate the expression of the seven pivotal ARGs.

CONCLUSION

In this study, based on seven ARGs, a risk model and nomogram established can be used for risk stratification and prediction of survival outcomes in patients with OSC, providing a reliable reference for individualized therapy of OSC patients.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma

Background

N6-methyladenosine (m⁶A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m⁶A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown.

Methods

The single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells.

Results

According to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m⁶A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m⁶A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m⁶A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74⁺CD44) ligand-receptor pairings facilitated communication between m⁶A-associated subtypes of TME cells and cancer cells.

Conclusion

Overall, our study demonstrated for the first time the function of m⁶A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

Multi-omics analysis of DNA replication-associated primase polymerase (PRIMPOL) in pan-cancer: a potential target for prognosis and immune response

BACKGROUND

It is critical to understand the mechanisms of human cancers in order to develop the effective anti-cancer therapeutic strategies. Recent studies indicated that primase polymerase (PRIMPOL) is strongly associated with the development of human cancers. Nevertheless, a systematic pan-cancer analysis of PRIMPOL remains to be further clarified.

METHOD

Comprehensive multi-omics bioinformatics algorithms, such as TIMER2.0, GEPIA2.0 and cBioPortal, were utilized to evaluate the biological roles of PRIMPOL in pan-cancer, including the expression profiles, genomic alterations, prognostic values and immune regulation.

RESULTS

PRIMPOL was upregulated in glioblastoma multiforme and kidney renal clear cell carcinoma. The brain lower grade glioma patients with enhanced PRIMPOL expression displayed poor prognostic values. We also demonstrated the PRIMPOL's immunomodulating effects on pan-cancer as well as its genomic changes and methylation levels. The aberrant expression of PRIMPOL was linked to various cancer-associated pathways, including DNA damage response, DNA repair, and angiogenesis, according to single-cell sequencing and function enrichment.

CONCLUSIONS

This pan-cancer analysis offers a thorough review of the functional roles of PRIMPOL in human cancers, suggesting PRIMPOL as a potentially important biomarker for the progression and immunotherapy of various cancers.

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Current evidence indicate that cancer-associated fibroblasts (CAFs) play an important role in prostate cancer (PCa) development and progression. In this study, we identified CAF-related molecular subtypes and prognostic index for PCa patients undergoing radical prostatectomy through integrating single-cell and bulk RNA sequencing data. We completed analyses using software R 3.6.3 and its suitable packages. Through single-cell and bulk RNA sequencing analysis, NDRG2, TSPAN1, PTN, APOE, OR51E2, P4HB, STEAP1 and ABCC4 were used to construct molecular subtypes and CAF-related gene prognostic index (CRGPI). These genes could clearly divide the PCa patients into two subtypes in TCGA database and the BCR risk of subtype 1 was 13.27 times higher than that of subtype 2 with statistical significance. Similar results were observed in MSKCC2010 and GSE46602 cohorts. In addtion, the molucular subtypes were the independent risk factor of PCa patients. We orchestrated CRGPI based on the above genes and divided 430 PCa patients in TCGA database into high- and low- risk groups according to the median value of this score. We found that high-risk group had significant higher risk of BCR than low-risk group (HR: 5.45). For functional analysis, protein secretion was highly enriched in subtype 2 while snare interactions in vesicular transport was highly enriched in subtype 1. In terms of tumor heterogeneity and stemness, subtype 1 showd higher levels of TMB than subtype 2. In addition, subtype 1 had significant higher activated dendritic cell score than subtype 2. Based on eight CAF-related genes, we developed two prognostic subtypes and constructed a gene prognostic index, which could predict the prognosis of PCa patients very well.