CCL19 associates with lymph node metastasis and inferior prognosis in patients with small cell lung cancer

The expression and prognostic value of CCL19 in breast cancer

BACKGROUND

Breast cancer ranks as the foremost cause of cancer-related mortality among women globally. Timely diagnosis stands as the most effective approach in mitigating breast cancer mortality rates. There exists a close relationship between immune processes and tumorigenesis. This study aims to elucidate the immune mechanisms and potential biomarkers associated with breast cancer using bioinformatics techniques.

OBJECTIVE

Initially, differentially expressed genes were identified through consensus analysis of invasive breast cancer (BRCA) samples sourced from The Cancer Genome Atlas (TCGA) database, focusing on immunotherapy response. Subsequently, protein-protein interaction (PPI) networks, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to refine the selection of potential genes. Lastly, expression and prognostic analyses of hub genes were conducted to identify reliable key genes, with a focus on CCL19. Immunohistochemistry (IHC) was employed to assess the differential expression of CCL19 in both tumor and adjacent breast tissue samples. Additionally, protein correlation analysis, signaling pathway analysis, immune infiltration analysis, gene co-expression analysis, and drug sensitivity analysis of CCL19 were conducted to investigate its pathological clinical features and potential biological functions.

RESULTS

CCL19 expression exhibited a significant increase in breast cancer. Elevated CCL19 expression correlates with advanced tumor stage and indicates a favorable prognosis in breast cancer. CCL19 expression correlates with the abundance of diverse tumor-infiltrating immune cells (TIICs). CCL19 exhibits a positive correlation with the expression of the majority of immune-related genes. Enrichment analysis revealed the involvement of CCL19 in immune-related pathways and the PI3K-Akt signaling pathway. These findings suggest that CCL19 may influence breast cancer prognosis through immune infiltration. Patients exhibiting high CCL19 expression demonstrated more favorable responses to immunotherapy.

CONCLUSION

Breast cancer demonstrates overexpression of CCL19. CCL19 holds promise as a biomarker for forecasting breast cancer prognosis and as a potential therapeutic target.

Role of tertiary lymphoid structures and B cells in clinical immunotherapy of gastric cancer

Gastric cancer is a common malignant tumor of the digestive tract, and its treatment remains a significant challenge. In recent years, the role of various immune cells in the tumor microenvironment in cancer progression and treatment has gained increasing attention. Immunotherapy, primarily based on immune checkpoint inhibitors, has notably improved the prognosis of patients with gastric cancer; however, challenges regarding therapeutic efficacy persist. Histological features within the tumor microenvironment, such as tertiary lymphoid structures (TLSs), tumor-infiltrating lymphocytes, and the proportion of intratumoral stroma, are emerging as potentially effective prognostic factors. In gastric cancer, TLSs may serve as local immune hubs, enhancing the ability of immune cells to interact with and recognize tumor antigens, which is closely linked to the effectiveness of immunotherapy and improved survival rates in patients. However, the specific cell type driving TLS formation in tumors has not yet been elucidated. Mature TLSs are B-cell regions containing germinal centers. During germinal center formation, B cells undergo transformations to become mature cells with immune function, exerting anti-tumor effects. Therefore, targeting B cells within TLSs could provide new avenues for gastric cancer immunotherapy. This review, combined with current research on TLSs and B cells in gastric cancer, elaborates on the relationship between TLSs and B cells in the prognosis and immunotherapy of patients with gastric cancer, aiming to provide effective guidance for precise immunotherapy.

Advances in biomarkers for immunotherapy in small-cell lung cancer

Small-cell lung cancer (SCLC) is a refractory cancer with rapid growth and high aggressiveness. Extensive-stage SCLC is initially sensitive to chemotherapy; however, drug resistance and recurrence occur rapidly, resulting in a poor survival outcome due to lack of subsequently efficient therapy. The emergence of immune checkpoint inhibitors (ICIs) generated a new landscape of SCLC treatment and significantly prolonged the survival of patients. However, the unselected immunotherapy restrains both beneficiary population and responsive period in SCLC compared to the other tumors. The complex tumor origin, high heterogeneity, and immunosuppressive microenvironment may disturb the value of conventional biomarkers in SCLC including programmed cell death 1 ligand 1 and tumor mutation burden. Transcriptional regulator-based subtypes of SCLC are current research hotspot, revealing that Y (I) subtype can benefit from ICIs. Additionally, molecules related to immune microenvironment, immunogenicity, epigenetics, and SCLC itself also indicated the therapeutic benefits of ICIs, becoming potential predictive biomarkers. In this review, we discussed the advances of biomarkers for prediction and prognosis of immunotherapy, promising directions in the future, and provide reference and options for precision immunotherapy and survival improvement in patients with SCLC.

Small cell lung cancer with liver metastases: from underlying mechanisms to treatment strategies

Small cell lung cancer (SCLC) represents an aggressive neuroendocrine (NE) tumor within the pulmonary region, characterized by very poor prognoses. Druggable targets for SCLC remain limited, thereby constraining treatment options available to patients. Immuno-chemotherapy has emerged as a pivotal therapeutic strategy for extensive-stage SCLC (ES-SCLC), yet it fails to confer significant efficacy in cases involving liver metastases (LMs) originating from SCLC. Therefore, our attention is directed towards the challenging subset of SCLC patients with LMs. Disease progression of LM-SCLC patients is affected by various factors in the tumor microenvironment (TME), including immune cells, blood vessels, inflammatory mediators, metabolites, and NE substances. Beyond standard immuno-chemotherapy, ongoing efforts to manage LMs in SCLC encompass anti-angiogenic therapy, radiotherapy, microwave ablation (MWA) / radiofrequency ablation (RFA), trans-arterial chemoembolization (TACE), and systemic therapies in conjunction with local interventions. Prospective experimental and clinical investigations into SCLC should prioritize precise and individualized approaches to enhance the prognosis across distinct patient cohorts.

DKK1+ tumor cells inhibited the infiltration of CCL19+ fibroblasts and plasma cells contributing to worse immunotherapy response in hepatocellular carcinoma

Intra-tumor immune infiltration plays a pivotal role in the interaction with tumor cells in hepatocellular carcinoma (HCC). However, its phenotype and related spatial structure remained elusive. To address these limitations, we conducted a comprehensive study combining spatial data (38,191 spots from eight samples) and single-cell data (56,022 cells from 20 samples). Our analysis revealed two distinct infiltration patterns: immune exclusion and immune activation. Plasma cells emerged as the primary cell type within intra-tumor immune clusters. Notably, we observed the co-location of CCL19+ fibroblasts with plasma cells, which secrete chemokines and promote T-cell activation and leukocyte migration. Conversely, in immune-exclusion samples, this co-location was primarily observed in the adjacent normal area. This co-localization correlated with T cell infiltration and the formation of tertiary lymphoid structures, validated by multiplex immunofluorescence conducted on twenty HCC samples. Both CCL19+ fibroblasts and plasma cells were associated with favorable survival outcomes. In an immunotherapy cohort, HCC patients who responded favorably exhibited higher infiltration of CCL19+ fibroblasts and plasma cells. Additionally, we observed the accumulation of DKK1+ tumor cells within the tumor area in immune-exclusion samples, particularly at the tumor boundary, which inhibited the infiltration of CCL19+ fibroblasts and plasma cells into the tumor area. Furthermore, in immune-exclusion samples, the SPP1 signaling pathway demonstrated the highest activity in communication between tumor and immune clusters, and CCL19-CCR7 played a pivotal role in the self-communication of immune clusters. This study elucidates immune exclusion and immune activation patterns in HCC and identifies relevant factors contributing to immune resistance.

Single-cell sequencing analysis reveals the dynamic tumour ecosystems of primary and metastatic lymph nodes in nasopharyngeal carcinoma

Lymph node metastasis contributed to the leading cause and treatment failure in nasopharyngeal carcinoma (NPC). The microenvironment and the cellular communications of lymph node metastasized tumours determine the tumour progression and therapeutic effect, but the ecosystems about the lymph node metastasis (LNM) for NPC patients remain poorly characterized. Here, we integrated the transcriptomes of 47,618 single cells from eight samples related to NPC LNM. The dynamic immune ecosystems and immunosuppressive microenvironment including T cells, myeloid cells and B cells were observed in the lymph node metastatic samples compared with primary tumours. Additionally, the heterogeneity of epithelial cells was also revealed, and several clusters with expression programs that were associated with the progression-free survival of NPC patients were identified. Additionally, our data revealed the complex intercellular communications from primary to lymph node metastasis. The rewiring of CCL signalling which plays an important role in tumour metastasis was further identified. Altogether, we systematically characterized the ecosystem of NPC primary and lymph node metastasized tumours, which may shed light on the development of a therapeutic strategy to improve clinical outcomes of NPC patients with lymph node metastasis.

Prognostic value and molecular mechanisms of OAS1 in lung adenocarcinoma

BACKGROUND

The expression of 2'-5'-oligoadenylate synthetase 1 (OAS1) in lung cancer has been validated in numerous studies. However, the prognostic value of OAS1 expression in lung adenocarcinoma (LUAD) still remains unclear. This study aimed to reveal the prognostic value and associated molecular mechanisms of OAS1 expression in LUAD.

METHODS

Gene expression data of LUAD were extracted from online databases. Gene and protein expression levels of OAS1 in LUAD and normal samples were revealed, followed by prognostic analysis of OAS1. Next, we conducted a thorough bioinformatics analysis to examine the enrichment of key functional and biological signaling pathways and their correlation with the abundance of immune cells. The independent prognoses, drug responses, and PPI networks associated with OAS1 were analyzed. OAS1 expression was evaluated in LUAD tissues and cell lines. OAS1 was knocked down by siRNA transfection, followed by CCK8, colony formation, and wound-healing assays.

RESULTS

Gene and protein expression levels of OAS1 in LUAD samples were significantly higher than those in normal samples (all P < 0.05). OAS1 stimulation were correlated with poor prognosis, lymph node metastasis, advanced tumor stage, immune cells, and immunomodulators. The prognostic value of OAS1 in LUAD was determined via univariate regression analysis. In total, 10 OAS1-associated genes were revealed via PPI analysis of OAS1, which were primarily enriched in functions, such as the negative regulation of viral genome replication. Transcriptional analysis revealed several OAS1-related interactions, including STAT3-miR-21-OAS1. STAT3 was overexpressed and miR-21 was expressed in LUAD cells. Upregulation of OAS1 protein was determined in LUAD tissues and cell lines. OAS1 knockdown significantly reduced proliferation and migration of LUAD cells.

CONCLUSIONS

OAS1 overexpression influenced survival and immune cell infiltration in patients with LUAD, which might be a potential prognostic gene for LUAD. Moreover, OAS1 contributed to LUAD progression by participating in STAT3-miR-21-OAS1 axis.

Exploring MiR-484 Regulation by Polyalthia longifolia: A Promising Biomarker and Therapeutic Target in Cervical Cancer through Integrated Bioinformatics and an In Vitro Analysis

BACKGROUND

MiR-484, implicated in various carcinomas, holds promise as a prognostic marker, yet its relevance to cervical cancer (CC) remains unclear. Our prior study demonstrated the Polyalthia longifolia downregulation of miR-484, inhibiting HeLa cells. This study investigates miR-484's potential as a biomarker and therapeutic target in CC through integrated bioinformatics and an in vitro analysis.

METHODS

MiR-484 levels were analyzed across cancers, including CC, from The Cancer Genome Atlas. The limma R package identified differentially expressed genes (DEGs) between high- and low-miR-484 CC cohorts. We assessed biological functions, tumor microenvironment (TME), immunotherapy, stemness, hypoxia, RNA methylation, and chemosensitivity differences. Prognostic genes relevant to miR-484 were identified through Cox regression and Kaplan-Meier analyses, and a prognostic model was captured via multivariate Cox regression. Single-cell RNA sequencing determined cell populations related to prognostic genes. qRT-PCR validated key genes, and the miR-484 effect on CC proliferation was assessed via an MTT assay.

RESULTS

MiR-484 was upregulated in most tumors, including CC, with DEGs enriched in skin development, PI3K signaling, and immune processes. High miR-484 expression correlated with specific immune cell infiltration, hypoxia, and drug sensitivity. Prognostic genes identified were predominantly epidermal and stratified patients with CC into risk groups, with the low-risk group showing enhanced survival and immunotherapeutic responses. qRT-PCR confirmed FGFR3 upregulation in CC cells, and an miR-484 mimic reversed the P. longifolia inhibitory effect on HeLa proliferation.

CONCLUSION

MiR-484 plays a crucial role in the CC progression and prognosis, suggesting its potential as a biomarker for targeted therapy.

CCL19: a novel prognostic chemokine modulates the tumor immune microenvironment and outcomes of cancers

BACKGROUND

CCL19 is a chemokine involved in cancer research due to its important role in the tumor microenvironment (TME) and clinical relevance in cancers. This study aimed to analyze transcription expression, genomic alteration, association with tumor immune microenvironment of CCL19 expression and its prediction value for prognosis and responses to immunotherapy for patients with cancers.

METHODS

RNA sequencing data and corresponding clinicopathological information of a total of large-scale cancer patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Multiplex immunofluorescence (mIF) was implemented to identify differential infiltration of Treg, CD8+ T cells, and tumor-associated macrophages, while CCL19 immunohistochemistry was conducted on 182 breast cancer samples from a real-world cohort.

RESULTS

Based on large-scale multi-center survival analysis of cancer patients, we found the prognosis of patients with high CCL19 expression was prominently better than those with low CCL19 expression. For patients from multiple independent cohorts, suppressed CCL19 expression exerts significant progressive phenotype and apoptosis activity of cancers, especially in breast and ovarian cancer. Interestingly, anti-tumor immune cells, specifically the CD8+ T cells and macrophages, were clustered from TME by elevated CCL19 expression. Additionally, higher CCL19 levels reflected heightened immune activity and substantial heterogeneity.

CONCLUSIONS

In conclusion, our findings support the notion that elevated CCL19 expression is linked to favorable outcomes and enhanced anti-tumor immunity, characterized by increased CD8+ T cells within the TME. This suggests the potential of CCL19 as a prognostic marker, predictive biomarker for immunotherapy, therapeutic target of cancers.

Emerging role of chemokines in small cell lung cancer: Road signs for metastasis, heterogeneity, and immune response

Small cell lung cancer (SCLC) is a recalcitrant, relatively immune-cold, and deadly subtype of lung cancer. SCLC has been viewed as a single or homogenous disease that includes deletion or inactivation of the two major tumor suppressor genes (TP53 and RB1) as a key hallmark. However, recent sightings suggest the complexity of SCLC tumors that comprises highly dynamic multiple subtypes contributing to high intratumor heterogeneity. Furthermore, the absence of targeted therapies, the understudied tumor immune microenvironment (TIME), and subtype plasticity are also responsible for therapy resistance. Secretory chemokines play a crucial role in immunomodulation by trafficking immune cells to the tumors. Chemokines and cytokines modulate the anti-tumor immune response and wield a pro-/anti-tumorigenic effect on SCLC cells after binding to cognate receptors. In this review, we summarize and highlight recent findings that establish the role of chemokines in SCLC growth and metastasis, and sophisticated intratumor heterogeneity. We also discuss the chemokine networks that are putative targets or modulators for augmenting the anti-tumor immune responses in targeted or chemo-/immuno-therapeutic strategies, and how these combinations may be utilized to conquer SCLC.

Reprogramming of sentinel lymph node microenvironment during tumor metastasis

Metastasis is a major cause of death in patients with cancer. The two main routes for cancer cell dissemination are the blood and lymphatic systems. The underlying mechanism of hematogenous metastasis has been well characterized in the past few decades. However, our understanding of the molecular basis of lymphatic metastasis remains at a premature stage. Conceptually, cancer cells invade into lymphatic capillary, passively move to collecting lymphatic vessels, migrate into sentinel lymph node (SLN;, the first lymph node to which cancer cells spread from the primary tumor), and enter the blood circulatory system via the subclavian vein. Before arriving, cancer cells release specific soluble factors to modulate the microenvironment in SLN to establish a beachhead for successful colonization. After colonization, cancer cells inhibit anti-tumor immunity by inducing the recruitment of regulatory T cell and myeloid-derived suppressor cells, suppressing the function of dendritic cell and CD8⁺ T cell, and promoting the release of immunosuppressive cytokines. The development of novel strategies to reverse cancer cell-triggered SLN remodeling may re-activate immunity to reduce beachhead buildup and distant metastasis. In addition to being a microanatomic location for metastasis, the SLN is also an important site for immune modulation. Nanotechnology-based approaches to deliver lymph node-tropic antibodies or drug-conjugated nanoparticles to kill cancer cells on site are a new direction for cancer treatment. Conversely, the induction of stronger immunity by promoting antigen presentation in lymph nodes provides an alternate way to enhance the efficacy of immune checkpoint therapy and cancer vaccine. In this review article, we summarize recent findings on the reprogramming of SLN during lymphatic invasion and discuss the possibility of inhibiting tumor metastasis and eliciting anti-tumor immunity by targeting SLN.

Identification of the Characteristic Genes and their Roles in Lung Adenocarcinoma Lymph Node Metastasis through Machine Learning Algorithm

Background. Lymph node metastasis is an important route of lung cancer metastasis and can significantly affect the survival of lung cancer. Methods. All the analysis was conducted out in the R software. Expression profile and clinical information of lung adenocarcinoma (LUAD) patients were downloaded from The Cancer Genome Atlas database. Results. In our study, we firstly identified the characteristic genes of lymph node metastasis in LUAD through two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) logistic regression, and SVM-RFE algorithms. Ten characteristic genes were finally identified, including CRHR2, ITIH1, PRSS48, MAS1L, CYP4Z1, LMO1, TCP10L2, KRT78, IGFBP1, and PITX3. Next, we performed univariate Cox regression, LASSO regression, and multivariate Cox regression sequentially to construct a prognosis model based on MAS1L, TCP10L2, and CRHR2, which had a good prognosis prediction efficiency in both training and validation cohorts. Univariate and multivariate analysis indicated that our model is a risk factor independent of other clinical features. Pathway enrichment analysis showed that in the high-risk patients, the pathway of MYC target, unfolded protein response, interferon alpha response, DNA repair, reactive oxygen species pathway, and glycolysis were significantly enriched. Among three model genes, MAS1L aroused our interest and therefore was selected for further analysis. KM survival curves showed that the patients with higher MAS1L might have better disease-free survival and progression-free survival. Further, pathway enrichment, genomic instability, immune infiltration, and drug sensitivity analysis were performed to in-deep explore the role of MAS1L in LUAD. Conclusions. Results showed that the signature based on MAS1L, TCP10L2, and CRHR2 is a useful tool to predict prognosis and lung cancer lymph node metastasis.