Tumor-infiltrating lymphocytes: Warriors fight against tumors powerfully

Comprehensive Evaluation of Frailty and Sarcopenia Markers to Predict Survival in Glioblastoma Patients

BACKGROUND

Glioblastoma (GBM) is the most common primary malignant brain tumour in adults. Patients with GBM are particularly susceptible to moderate-to-high frail. Frailty status has been associated with the outcome of many types of cancer, including GBM, although there is still little consensus regarding the specific criteria for assessing frailty status. This study aimed to determine the predictive significance of the modified frailty score (mFS) in GBM patients using haematological and sarcopenia indicators.

METHODS

Between January 2016 and September 2022, we enrolled 309 adult GBM patients. Data on demographics, haematological examination, and temporal muscle thickness (TMT) were collected and assessed. The prognostic relevance of the frailty parameters was established using Kaplan-Meier and Cox proportional model. The scoring systems were created by integrating these indicators. Variables with independent prognostic values were used to construct the nomograms. Nomogram accuracy was evaluated using the calibration curve, Harrell's concordance index (C-index), and time-dependent receiver operating characteristic curves. Clinical practicality was assessed using decision curve analysis.

RESULTS

The baseline characteristics of the 309 participants revealed a median age of 59 years (interquartile range 52-66) with a predominance of male patients (58.58%). TMT (hazard ratio [HR] = 3.787, 95% confidence interval [CI] 2.576-5.566, p < 0.001), prognostic nutritional index (HR = 1.722, 95% CI 1.098-2.703, p = 0.018), and mean corpuscular volume (HR = 1.958, 95% CI 1.111-3.451, p = 0.020) were identified as independent prognostic markers. The constructed mFS, obtained by integrating these three indices, exhibited independent prognostic significance (HR = 2.461, 95% CI 1.751-3.457, p < 0.001). The patients in the low-risk group had a median overall survival (OS) of 13.9 months, while the patients in the high risk had a median OS of 5.8 months. Importantly, the mFS demonstrated significant independent prognostic value in the subgroup aged > 65 (HR = 1.822, 95% CI 1.011-3.284, p = 0.046). The nomogram, which included the mFS, demonstrated high accuracy, with a c-index of 0.781. The nomogram bootstrapped calibration plot also performed well compared to the ideal model. Nomograms showed promising discriminative potential, with time-dependent areas under the curves of 0.945, 0.835, and 0.820 for 0.5-, 1-, and 2-year overall survival prediction, respectively.

CONCLUSIONS

Preoperative mFS is a comprehensive frailty marker for predicting survival outcomes in patients with GBM. A dynamic nomogram incorporating the mFS may facilitate preoperative survival evaluation. Early and appropriate multimodal interventions, including nutritional support, rehabilitation, and psychological care, may help in the neurosurgical care of patients with GBM or other brain tumours.

Tumor-promoting effect and tumor immunity of SRSFs

Serine/arginine-rich splicing factors (SRSFs) are a family of 12 RNA-binding proteins crucial for the precursor messenger RNA (pre-mRNA) splicing. SRSFs are involved in RNA metabolism events such as transcription, translation, and nonsense decay during the shuttle between the nucleus and cytoplasm, which are important components of genome diversity and cell viability. SRs recognize splicing elements on pre-mRNA and recruit the spliceosome to regulate splicing. In tumors, aberrant expression of SRSFs leads to aberrant splicing of RNA, affecting the proliferation, migration, and anti-apoptotic ability of tumor cells, highlighting the therapeutic potential of targeted SRSFs for the treatment of diseases. The body's immune system is closely related to the occurrence and development of tumor, and SRSFs can affect the function of immune cells in the tumor microenvironment by regulating the alternative splicing of tumor immune-related genes. We review the important role of SRSFs-induced aberrant gene expression in a variety of tumors and the immune system, and prospect the application of SRSFs in tumor. We hope that this review will inform future treatment of the disease.

Advancing biliary tract malignancy treatment: emerging frontiers in cell-based therapies

Biliary tract malignancies, including intrahepatic cholangiocarcinoma, extrahepatic cholangiocarcinoma, and gallbladder cancer, represent a group of aggressive cancers with poor prognosis due to late-stage diagnosis, limited treatment options, and resistance to conventional therapies like chemotherapy and radiotherapy. These challenges emphasize the urgent need for innovative therapeutic approaches. In recent years, cell-based therapies have emerged as a promising avenue, offering potential solutions through immune modulation, genetic engineering, and targeted intervention in the tumor microenvironment. This Mini-review provides an overview of current advancements in cell-based therapies for biliary malignancies, encompassing immune cell-based strategies such as CAR-T cells, NK cells, dendritic cell vaccines, and tumor-infiltrating lymphocytes. We also examine strategies to overcome the immunosuppressive tumor microenvironment and discuss the integration of cell therapies into multimodal treatment regimens. By synthesizing preclinical and clinical findings, this review highlights key insights and future directions, aiming to assist researchers and clinicians in translating these approaches into effective treatments. The transformative potential of cell-based therapies discussed here makes this review a valuable resource for advancing biliary malignancy research and clinical applications.

Response Gene to Complement 32 is associated with poor patient survival and an inflamed tumor-immune microenvironment in clear cell renal cell carcinoma

It has been well established that tumor-infiltrating lymphocytes (TILs) play a critical role in the pathogenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the mechanism on the interactions between TILs and tumor cells in the tumor-immune microenvironment remains unclear. In the present study, the expression of Response Gene to Complement 32 (RGC-32) was evaluated using immunohistochemistry. We analyzed the associations of RGC-32 expression with patient characteristics and survival. We also assessed TILs and their subsets (CD3+, CD4+, CD8+ and PD-1+) in the tumor nest. The level of RGC-32 expression was positively correlated with ISUP grade and Ki67 expression and was an independent poor prognosis factor of patients with ccRCC. RGC-32 expression was negatively correlated with the infiltration of TIL and CD3+T cells, but positively correlated with infiltration of PD-1+cells. In vitro studies showed that RGC-32 expression in renal cancer cells was downregulated by activated immune cells. Further investigation revealed that RGC-32 expression in renal cancer cells was inhibited by TNF-α and IL-1β secreted by activated immune cells. Collectively, these data indicate that RGC-32 could be a novel prognostic and druggable target related to the tumor-immune microenvironment in renal cancer.

The Prognostic Significance of the CALLY Index in Ampullary Carcinoma: An Inflammation-Nutrition Retrospective Analysis

Background

As a novel inflammatory-nutritional biomarker, the C-reactive protein-albumin-lymphocyte (CALLY) index has demonstrated significant prognostic value in various malignancies. However, research on its association with the prognosis of ampullary carcinoma (AC) is rare. This study aims to investigate the relationship between the CALLY index and the prognosis of patients with AC.

Methods

We retrospectively analyzed data from 201 patients with AC at Sun Yat-sen University Cancer Center. Several clinicopathological factors and biomarkers were included in the study. Univariate and multivariate Cox regression analyses, along with competing risk analysis, were performed to identify prognostic factors for AC after pancreaticoduodenectomy (PD). Only factors with significant results in univariate analysis were included in multivariate analysis. To ensure the robustness of our findings, propensity score matching (PSM) analyses were conducted to assess survival differences according to the CALLY index.

Results

The univariate and multivariate Cox regression analyses revealed that pathological type, N stage, T stage, postoperative chemotherapy regimen, and the CALLY index were all statistically significant prognostic factors for patients with AC after PD (all P values < 0.05). Taking into account non-cancer-related mortality as competing hazards, these factors remained significant predictors (all P values < 0.05). After PSM, the survival advantage observed between the low and high CALLY groups remained discernible and consistent.

Conclusion

This study indicated that a reduced CALLY index correlates with a poorer cancer-specific survival in AC patients after PD, highlighting its utility as a prognostic marker for this condition.

Stroma-and Tumor-Associated Predictive Features in Salivary Gland Adenoid Cystic Carcinoma of the Head and Neck

BACKGROUND

There is lack of knowledge on the utility of prognostic histopathologic characteristics in adenoid cystic carcinoma (ACC) of the head and neck. We evaluated the prognostic value of tumor and stroma-related histopathologic features in ACC.

MATERIALS AND METHODS

A total of 65 cases of ACC from minor and major salivary glands were included in this study. We evaluated tumor budding, tumor-infiltrating lymphocytes (TILs), and tumor-stroma ratio (TSR) in hematoxylin and eosin (HE) stained sections.

RESULTS

Stroma-rich ACCs recurred more frequently (p = 0.029) during follow-up and associated with distant metastasis (p = 0.038). In multivariable analysis, stroma-rich tumors associated with poorer disease-specific survival with a hazard ratio of 3.76 (95% CI 1.10-12.83, p = 0.034). ACCs commonly showed a low infiltration of TILs as 89% of the tumors was characterized by an immune desert pattern. Low infiltration of TILs associated significantly with increased tumor budding (p = 0.039).

CONCLUSION

Adverse features of TSR and tumor budding are widely expressed in ACC, and stroma-rich tumors are associated with poor prognosis. Low number of TILs in ACC tissue indicates a weak immune response by the host and illustrates the nature of ACC as a relentless malignancy.

A pump-free microfluidic co-culture system for investigating NK cell-tumor spheroid interactions in flow conditions

Natural killer (NK) cells are pivotal in immunotherapy due to their potent tumor-targeting capabilities. However, accessible in vitro 3D dynamic models for evaluating Tumor Infiltrating Natural Killer Cells (TINKs) remain scarce. This study addresses this gap by developing a novel pump-free microfluidic chip to investigate the interactions between NK-92 cells and prostate DU 145 tumor spheroids. The platform facilitates the separation of free NKs and TINKs for subtype characterization. The design integrates multiple planes with a multi-layer paper scaffold to accommodate tumor spheroids, allowing NK-92 cells to traverse Matrigel-coated barriers that mimic the extracellular matrix. The dual-channel pump-free device enables unidirectional circulation of NK-92 cells, allowing analysis of tumor spheroid movement and NK-92 cell interactions under flow conditions. Results demonstrate continuous fluid circulation in the dual-channel device by rocking the platform at tilt angles of 21° and 15°. Tumor spheroids show- enhanced migration under flow conditions compared to static culture. Although spheroids recruit slightly more NK-92 cells under flow conditions, CD56 and CD16 receptor expression on IL-2-activated free NK-92 cells and tumor-infiltrating NK-92 cells matches in vivo patterns in dynamic cultures. These findings suggest that tumor cells and fluid dynamics significantly influence NK cell subtypes. This pump-free microfluidic platform is a functional tool for simulating and studying immune cell-tumor interactions, providing valuable insights into NK cell dynamics with tumor spheroids in physiologically relevant environments.

Preoperative inflammatory burden index for prognostication in esophageal squamous cell carcinoma undergoing radical resection

BACKGROUND

The Inflammatory burden Index (IBI) is an effective predictor for a range of malignancies. However, the significance of IBI in esophageal squamous cell carcinoma (ESCC) needs to be further verified. The aim of this study was to verify the predictive power of IBI in ESCC undergoing radical resection.

METHODS

The current retrospective study, which comprised 408 ESCC patients randomized into either the primary or validation cohort, evaluated the relationships between IBI, clinical characteristics, and cancer-specific survival (CSS). Additionally, the nomogram model was also constructed and verified.

RESULTS

The IBI is significantly related to tumor length, vessel invasion, perineural invasion, and TNM stage. Compared to other hematological indices, the decision curve analyses (DCA) and receiver operating characteristic curve (ROC) confirmed the higher prognostic value of IBI, indicating the better clinical applicability. In patients with high IBI compared to the low IBI cohort, the 5-year CSS was considerably worse (total: 27.0% vs. 59.1%, P < 0.001; primary: 25.0% vs. 58.9%, P < 0.001; validation: 31.7% vs. 59.7%, P = 0.002). The IBI was shown to be an independent parameter by multivariate analyses (primary: HR = 2.352, P < 0.001; validation: HR = 1.683, P = 0.045). Finally, with the C-index of 0.675 (0.656-0.695) in the primary set and 0.662 (0.630-0.694) in the validation set for CSS in ESCC, an IBI-based nomogram was created and validated.

CONCLUSION

The predictive significance of IBI in ESCC patients undergoing radical resection was validated by this investigation. IBI may be utilized for preoperative evaluation of ESCC as it was found to be substantially correlated with prognosis.

Development and application of a predictive model for survival and drug therapy based on COVID-19-related lncRNAs in non-small cell lung cancer

Numerous studies have substantiated the pivotal role of long non-coding RNAs (lncRNAs) in the progression of non-small cell lung cancer (NSCLC) and the prognosis of afflicted patients. Notably, individuals with NSCLC may exhibit heightened vulnerability to the novel coronavirus disease (COVID-19), resulting in a more unfavorable prognosis subsequent to infection. Nevertheless, the impact of COVID-19-related lncRNAs on NSCLC remains unexplored. The aim of our study was to develop an innovative model that leverages COVID-19-related lncRNAs to optimize the prognosis of NSCLC patients. Pertinent genes and patient data were procured from reputable databases, including TCGA, Finngen, and RGD. Through co-expression analysis, we identified lncRNAs associated with COVID-19. Subsequently, we employed univariate, LASSO, and multivariate COX regression techniques to construct a risk model based on these COVID-19-related lncRNAs. The validity of the risk model was assessed using KM analysis, PCA, and ROC. Furthermore, functional enrichment analysis was conducted to elucidate the functional pathways linked to the identified lncRNAs. Lastly, we performed TME analysis and predicted the drug sensitivity of the model. Based on risk scores, patients were categorized into high- and low-risk subgroups, revealing distinct clinicopathological factors, immune pathways, and chemotherapy sensitivity between the subgroups. Four COVID-19-related lncRNAs (AL161431.1, AC079949.1, AC123595.1, and AC108136.1) were identified as potential candidates for constructing prognostic prediction models for NSCLC. We also observed a positive correlation between risk score and MDSC, exclusion, and CAF. Additionally, two immune pathways associated with high-risk and low-risk subgroups were identified. Our findings further support the association between COVID-19 infection and neuroactive ligand-receptor interaction, as well as steroid metabolism in NSCLC. Moreover, we identified several highly sensitive chemotherapy drugs for NSCLC treatment. The developed model holds significant value in predicting the prognosis of NSCLC patients and guiding treatment decisions.

Advances in cell therapy: progress and challenges in hematological and solid tumors

Cell-based therapies harness the endogenous ability of the immune system to fight cancer and have shown promising results in the treatment of hematological malignancies. However, their clinical application beyond B cell malignancies is hampered by numerous hurdles, ranging from relapsed disease to a hostile tumor microenvironment (TME). Recent advances in cell engineering and TME modulation may expand the applicability of these therapies to a wider range of cancers, creating new treatment possibilities. Breakthroughs in advanced gene editing and sophisticated cell engineering, have also provided promising solutions to longstanding challenges. In this review, we examine the challenges and future directions of the most prominent cell-based therapies, including chimeric antigen receptor (CAR)-T cells, tumor-infiltrating lymphocytes (TILs), and natural killer (NK) cells, and emerging modalities. We provide a comprehensive analysis of emerging cell types and combination strategies translated into clinical trials, offering insights into the next generation of cell-based cancer treatments.

Into the Future: Fighting Melanoma with Immunity

Immunotherapy offers a novel and promising option in the treatment of late-stage melanoma. By utilizing the immune system to assist in tumor destruction, patients have additional options after tumor progression. Immune checkpoint inhibitors reduce the ability for tumors to evade the immune system by inhibiting key surface proteins used to inactivate T-cells. Without these surface proteins, T-cells can induce cytotoxic responses against tumors. Tumor infiltrating lymphocyte therapy is a form of adoptive cell therapy that takes advantage of a small subset of T-cells that recognize and infiltrate tumors. Isolation and rapid expansion of these colonies assist the immune system in mounting a charged response that can induce remission. Tumor vaccines deliver a high dose of unique antigens expressed by tumor cells to the entire body. The introduction of large quantities of tumor antigens upregulates antigen presenting cells and leads to effective activation of the immune system against tumors. Cytokine therapy introduces high amounts of chemical messengers that are endogenous to the immune system and support T-cell expansion. While other methods of immunotherapy exist, immune checkpoint inhibitors, tumor infiltrating lymphocytes, tumor vaccines, and cytokine therapy are commonly used to treat melanoma. Like many other cancer treatments, immunotherapy is not without adverse effects, as toxicities represent a major obstacle. However, immunotherapy has been efficacious in the treatment of melanoma.

The Potential of PD-1 and PD-L1 as Prognostic and Predictive Biomarkers in Colorectal Adenocarcinoma Based on TILs Grading

AIM

Colorectal cancer (CRC) is a prevalent malignancy with a high mortality rate. Tumor-infiltrating lymphocytes (TILs) play a crucial role in the immune response against tumors. Programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) are key immune checkpoints regulating T cells in the tumor microenvironment. This study aimed to assess the relationships among PD-1 expression on TILs, PD-L1 expression in tumors, and TIL grading in colorectal adenocarcinoma.

METHODS

A cross-sectional design was employed to analyze 130 colorectal adenocarcinoma samples. The expression of PD-1 and PD-L1 was assessed through immunohistochemistry. A semi-quantitative scoring system was applied. Statistical analysis with the chi-square test was performed to explore correlations, with the data analyzed in SPSS version 27.

RESULTS

PD-1 expression on TILs significantly correlated with a higher TIL grading (p < 0.001), while PD-L1 expression in tumors showed an inverse correlation with TIL grading (p < 0.001).

CONCLUSIONS

The expression of PD-1 on TILs and PD-L1 on tumor cells correlated significantly with the grading of TILs in colorectal adenocarcinoma. This finding shows potential as a predictive biomarker for PD-1/PD-L1 blockade therapy. Further studies are needed to strengthen these results.

Transcription Factor Forkhead Box Protein 3 (FOXP3) as a Prognostic Indicator for Postoperative Outcomes in Patients with Breast Cancer: Establishment of a Prognostic Nomogram

Purpose

The current investigation is to assess FOXP3 expression in breast cancer patients and evaluate the predictive significance of FOXP3.

Patients and Methods

A cohort of 313 cases between January 2015 and November 2015 were enrolled this research. Immunohistochemistry (IHC) assay was utilized to detect the expression levels of FOXP3 in primary breast carcinoma specimens. These patients were separated into two groups by semiquantitative scoring approach. Chi-square test and Fisher's exact test were conducted to investigate the correlations between FOXP3 expression in tumors and clinicopathological variables. Kaplan-Meier method and Log rank test were utilized to generate survival curves for disease-free survival (DFS) and overall survival (OS). The independent factors were examined using Cox regression analysis. Nomogram models were created for assessing DFS and OS rates.

Results

Depending on the levels of FOXP3 expression in tumors, these patients were categorized into two groups: low FOXP3 expression (174 cases) and high FOXP3 expression (139 cases). The patients exhibiting low levels of FOXP3 expression in tumors demonstrated a longer survival duration contrasted with those with high expression (DFS: 88.75 vs 65.87 months, χ2=36.1100, P<0.0001; OS: 89.70 vs 78.37 months, χ2=32.4900, P<0.0001). Multivariate analysis revealed that FOXP3 was a significant prognostic factor [DFS: hazard ratio (HR): 2.822, 95% CI: 1.595-4.992, P<0.0001; OS: HR: 3.232, 95% CI: 1.812-5.763, P<0.0001]. The good predictive clinical utility of FOXP3-based nomograms within the threshold probability range for different survival rates was demonstrated by calibration curve and decision curve analyses.

Conclusion

FOXP3 expression serves as a crucial prognostic indicator in breast cancer patients, and may aid preoperative evaluation in clinical practice.

SEMA7A as a Novel Prognostic Biomarker and Its Correlation with Immune Infiltrates in Breast Cancer

Background

The role of Semaphorin 7a (SEMA7A) in the initiation and progression of different types of cancerous lesions has been extensively studied. However, the prognostic significance of SEMA7A, specifically in breast cancer (BC), lacks clarity.

Methods

We conducted an evaluation on the relationship between SEMA7A and the prognosis, immune invasion and tumor mutation burden in different types of cancer by analyzing data from The Cancer Genome Atlas database. The present study focused on investigating the expression level, mutation, immune correlation and coexpression of SEMA7A in BC, utilizing various databases such as the University of Alabama at Birmingham Cancer data analysis portal, cBioPortal and tumor immune estimation resource. Survival analysis was carried out using the Kaplan-Meier Plotter. Furthermore, we employed the R software package to generate receiver operating characteristic (ROC) curves and nomograms. Notably, P<0.05 was considered to indicate statistical significance.

Results

Using pancancer analysis, it has been observed that the expression of SEMA7A is elevated in various types of cancer and is strongly correlated with the prognosis of different cancer types. SEMA7A also exhibits a significant association with the tumor mutation burden of diverse types of cancer. Moreover, SEMA7A displays a notable increase in BC cases, and was indicated to have a substantial association with the abundance of immune infiltration. In-depth survival analysis demonstrated that elevated levels of SEMA7A expression are notably linked to shorter overall survival and distant metastasis-free survival among patients with BC. The efficiency of SEMA7A as a reliable prognostic biomarker for BC has been substantiated by the validation of ROC curves and nomograms.

Conclusion

SEMA7A has the potential to function as a prognostic indicator for BC, and its correlation with immune infiltration in BC is significant.

An abnormal metabolism-related gene, ALG3, is a potential diagnostic and prognostic biomarker for lung adenocarcinoma

BACKGROUND

To explore the abnormal metabolism-related genes that affect the prognosis of patients with lung adenocarcinoma (LUAD), and analyze the relationship with immune infiltration and competing endogenous RNA (ceRNA) network.

METHODS

Transcriptome data of LUAD were downloaded from the Cancer Genome Atlas database. Abnormal metabolism-related differentially expressed genes in LUAD were screened by the R language. Cox analysis was used to construct LUAD prognostic risk model. Kaplan-Meier test, ROC curve and nomograms were used to evaluate the predictive ability of metabolic related gene prognostic model. CIBERSORT algorithm was used to analyze the relationship between risk score and immune infiltration. The starBase database constructed a regulatory network consistent with the ceRNA hypothesis. IHC experiments were performed to verify the differential expression of ALG3 in LUAD and paracancerous samples.

RESULTS

In this study, 42 abnormal metabolism-related differential genes were screened. After survival analysis, the final 5 metabolism-related genes were used as the construction of prognosis model, including ALG3, COL7A1, KL, MST1, and SLC52A1. In the model, the survival rate of LUAD patients in the high-risk subgroup was lower than that in the low-risk group. In addition, the risk score of the constructed LUAD prognostic model can be used as an independent prognostic factor for patients. According to the analysis of CIBERSORT algorithm, the risk score is related to the infiltration of multiple immune cells. The potential ceRNA network of model genes in LUAD was constructed through the starBase database. IHC experiments revealed that ALG3 expression was upregulated in LUAD.

CONCLUSION

The prognostic model of LUAD reveals the relationship between metabolism and prognosis of LUAD, and provides a novel perspective for diagnosis and research of LUAD.

Recent Advancements in Cell-Based Therapies in Melanoma

Malignant melanoma outcomes have drastically changed in recent years due to the introduction of immune checkpoint inhibitors (ICIs). However, many patients still experience intolerable side effects, therapy resistance, and disease progression on ICI therapy. Therefore, there remains a need for novel therapeutics that address this gap in treatment options. Cell-based therapies have gained wide attention as a therapeutic option that could address this gap in treatment options for advanced melanoma. These therapies work by extracting certain cell types produced in the human body such as T-cells, modifying them based on a specific target, and transfusing them back into the patient. In the realm of cancer therapy, cell-based therapies utilize immune cells to target tumor cells while sparing healthy cells. Recently, the Food and Drug Administration (FDA) has approved the usage of lifileucel, a tumor-infiltrating lymphocyte (TIL) therapy, in advanced melanoma. This came following recent results from the C-144-01 study (NCT02360579), which demonstrated the efficacy and safety of TILs in metastatic melanoma patients who otherwise failed on standard ICI/targeted therapy. Thus, the results of this trial as well as the recent FDA approval have proven the viability of utilizing cell-based therapies to fill the gap in treatment options for patients with advanced melanoma. This review aims to provide a comprehensive overview of major cell-based therapies that have been utilized in melanoma by delineating results of the most recent multi-center phase II/ III clinical trials that evaluate the efficacy and safety of major cell-based therapies in melanoma. Additionally, we provide a summary of current limitations in each cell-based therapeutic option as well as a future direction of how to further extrapolate these cell-based therapies in advanced melanoma.

Photonanozyme-Kras-ribosome combination treatment of non-small cell lung cancer after COVID-19

With the outbreak of the coronavirus disease 2019 (COVID-19), reductions in T-cell function and exhaustion have been observed in patients post-infection of COVID-19. T cells are key mediators of anti-infection and antitumor, and their exhaustion increases the risk of compromised immune function and elevated susceptibility to cancer. Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer with high incidence and mortality. Although the survival rate after standard treatment such as surgical treatment and chemotherapy has improved, the therapeutic effect is still limited due to drug resistance, side effects, and recurrence. Recent advances in molecular biology and immunology enable the development of highly targeted therapy and immunotherapy for cancer, which has driven cancer therapies into individualized treatments and gradually entered clinicians' views for treating NSCLC. Currently, with the development of photosensitizer materials, phototherapy has been gradually applied to the treatment of NSCLC. This review provides an overview of recent advancements and limitations in different treatment strategies for NSCLC under the background of COVID-19. We discuss the latest advances in phototherapy as a promising treatment method for NSCLC. After critically examining the successes, challenges, and prospects associated with these treatment modalities, their profound prospects were portrayed.

Combination of transcriptome and Mendelian inheritance reveals novel prognostic biomarker of CTLA-4-related lncRNAs and protective role of nitrogen metabolism pathway in lung adenocarcinoma development

OBJECTIVE

Since in the cancer setting, tumor cells may use cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to evade the immune system. This study aimed to identify CTLA-4-related long non-coding RNAs (lncRNAs) and assess their roles in lung adenocarcinoma (LUAD) development.

METHODS

Clinical and genomic data were obtained from The Cancer Genome Atlas (TCGA), MSigDB and Gene Weaver. CTLA-4-related lncRNA-based gene signatures (CTLA4LncSigs) were identified using Cox regression, establishing a risk score model and an independent prognostic model. Enrichment analysis (GO/KEGG) was performed. Mendelian randomization (MR) analysis investigated the nitrogen metabolism and lung cancer relationship, with Bayesian weighted MR (BWMR) addressing uncertainties. Correlations with tumor microenvironment and drug sensitivity were explored.

RESULTS

Nineteen CTLA4LncSigs significantly influenced LUAD prognosis. The risk score demonstrated independence as a prognostic factor. Functional analysis revealed lncRNAs' impact on nitrogen metabolism. MR and BWMR confirmed the protective role of the nitrogen metabolism pathway in lung cancer.

CONCLUSION

Our study identifies CTLA-4-related lncRNAs associated with LUAD prognosis and uncovers a previously undiscovered protective role of the nitrogen metabolism pathway in combating LUAD development, providing new insights into potential therapeutic targets and prognostic biomarkers for this aggressive cancer subtype.

Immunotherapy for hepatocellular carcinoma

ABSTRACT

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Its high recurrence rate and lack of effective control drugs result in a 5-year survival rate of only about 10%. HCC is a tumor regulated by the immune system. Significant breakthroughs have occurred in treating solid tumors with immunotherapy in recent years. Various immunotherapies, such as immune checkpoint inhibitors (ICIs), including combination therapies, have demonstrated promising therapeutic effects in both clinical applications and research. Other immunotherapies, such as adoptive cell therapies and oncolytic viruses, are also emerging, offering hope for addressing long-term survival issues in HCC. This article reviews current commonly used immunotherapy strategies and the latest research findings for reference.

Cancer immunotherapy and its facilitation by nanomedicine

Cancer immunotherapy has sparked a wave of cancer research, driven by recent successful proof-of-concept clinical trials. However, barriers are emerging during its rapid development, including broad adverse effects, a lack of reliable biomarkers, tumor relapses, and drug resistance. Integration of nanomedicine may ameliorate current cancer immunotherapy. Ultra-large surface-to-volume ratio, extremely small size, and easy modification surface of nanoparticles enable them to selectively detect cells and kill cancer cells in vivo. Exciting synergistic applications of the two approaches have emerged in treating various cancers at the intersection of cancer immunotherapy and cancer nanomedicine, indicating the potential that the combination of these two therapeutic modalities can lead to new paradigms in the treatment of cancer. This review discusses the status of current immunotherapy and explores the possible opportunities that the nanomedicine platform can make cancer immunotherapy more powerful and precise by synergizing the two approaches.

CAR-T therapy for ovarian cancer: Recent advances and future directions

Ovarian cancer (OC) is a common gynecological tumor with high mortality, which is difficult to control its progression with conventional treatments and is prone to recurrence. Recent studies have identified OC as an immunogenic tumor that can be recognized by the host immune system. Immunotherapy for OC is being evaluated, but approaches such as immune checkpoint inhibitors have limited efficacy, adoptive cell therapy is an alternative therapy, in which CAR(chimeric antigen receptor)-T therapy has been applied to the clinical treatment of hematological malignancies. In addition, CAR-NK and CAR-macrophage (CAR-M) have also shown great potential in the treatment of solid tumors. Here, we discuss recent advances in preclinical and clinical studies of CAR-T for OC treatment, introduce the efforts made by researchers to modify the structure of CAR in order to achieve effective OC immunotherapy, as well as the research status of CAR-NK and CAR-M, and highlight emerging therapeutic opportunities that can be utilized to improve the survival of patients with OC using CAR-based adoptive cell therapy.

Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells

The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies.

Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

The Role of Short-Chain Fatty Acids, Particularly Butyrate, in Oncological Immunotherapy with Checkpoint Inhibitors: The Effectiveness of Complementary Treatment with Clostridium butyricum 588

The discovery of immune checkpoints (CTLA-4, PD-1, and PD-L1) and their impact on the prognosis of oncological diseases have paved the way for the development of revolutionary oncological treatments. These treatments do not combat tumors with drugs "against" cancer cells but rather support and enhance the ability of the immune system to respond directly to tumor growth by attacking the cancer cells with lymphocytes. It has now been widely demonstrated that the presence of an adequate immune response, essentially represented by the number of TILs (tumor-infiltrating lymphocytes) present in the tumor mass decisively influences the response to treatments and the prognosis of the disease. Therefore, immunotherapy is based on and cannot be carried out without the ability to increase the presence of lymphocytic cells at the tumor site, thereby limiting and nullifying certain tumor evasion mechanisms, particularly those expressed by the activity (under positive physiological conditions) of checkpoints that restrain the response against transformed cells. Immunotherapy has been in the experimental phase for decades, and its excellent results have made it a cornerstone of treatments for many oncological pathologies, especially when combined with chemotherapy and radiotherapy. Despite these successes, a significant number of patients (approximately 50%) do not respond to treatment or develop resistance early on. The microbiota, its composition, and our ability to modulate it can have a positive impact on oncological treatments, reducing side effects and increasing sensitivity and effectiveness. Numerous studies published in high-ranking journals confirm that a certain microbial balance, particularly the presence of bacteria capable of producing short-chain fatty acids (SCFAs), especially butyrate, is essential not only for reducing the side effects of chemoradiotherapy treatments but also for a better response to immune treatments and, therefore, a better prognosis. This opens up the possibility that favorable modulation of the microbiota could become an essential complementary treatment to standard oncological therapies. This brief review aims to highlight the key aspects of using precision probiotics, such as Clostridium butyricum, that produce butyrate to improve the response to immune checkpoint treatments and, thus, the prognosis of oncological diseases.

The therapeutic effect and targets of herba Sarcandrae on breast cancer and the construction of a prognostic signature consisting of inflammation-related genes

Background

The prevalence of breast cancer (BRCA), which is common among women, is on the rise. This study applied network pharmacology to explore the potential mechanism of action of herba sarcandrae in BRCA and construct a prognostic signature composed of inflammation-related genes.

Methods

The active ingredients of herba sarcandrae were screened using the SymMap, TCMID, and TCMSP platforms, and the molecular targets were determined in the UniProt database. The "drug-active compound-potential target" network was established with Cytoscape 3.7.2. The molecular targets were subjected to disease ontology, gene ontology (GO), and Kyoto Encyclopedia of Genes (KEGG) analyses. AutoDock software was used for molecular docking. Differentially expressed genes (DEGs) related to inflammation were obtained from the BRCA Cancer Genome Atlas (TCGA) database. In the training cohort, the univariate Cox regression model was applied to preliminarily screen prognostic genes. A multigene signature was built by the least absolute shrinkage and selection operator (LASSO) regression model, followed by validation through Kaplan‒Meier, Cox, and receiver operating characteristic (ROC) analyses.

Results

Forty-one active compounds were identified, and 265 therapeutic targets for herba sarcandrae were predicted. GO enrichment results revealed significant enrichment of biological processes, such as response to xenobiotic stimuli, response to nutrient levels, and response to lipopolysaccharide. KEGG analysis revealed significant enrichment of pathways such as AGE-RAGE and chemical carcinogenesis receptor activation signaling pathways. In addition, the herbs Marc-Andre and rutin were shown to mediate BRCA cell proliferation and apoptosis via the interferon regulatory factor 1 (IRF1)/signal transducer and activator of transcription 3 (STAT3)/programmed death-ligand 1 (PD-L1) pathway. Sixteen inflammatory signatures, including BST2, GPR132, IL12B, IL18, IL1R1, IL2RB, IRF1, and others, were constructed, and the risk score was found to be a strong independent prognostic factor for overall survival in BRCA patients. The 16-inflammation signature was associated with several clinical features (age, clinical stage, T, and N classifications) and could reflect immune cell infiltration in tumor microenvironments with different immune cells.

Conclusions

Herba sarcandrae and rutin were shown to mediate BRCA cell proliferation and apoptosis via the IRF1/STAT3/PD-L1 pathway, and the 16-member inflammatory signature might be a novel biomarker for predicting BRCA patient prognosis, providing more accurate guidance for clinical treatment prognosis evaluation and having important reference value for individualized treatment selection.

Nanomaterials in modulating tumor-associated macrophages and enhancing immunotherapy

Tumor-associated macrophages (TAMs) are predominantly present in the tumor microenvironment (TME) and play a crucial role in shaping the efficacy of tumor immunotherapy. These TAMs primarily exhibit a tumor-promoting M2-like phenotype, which is associated with the suppression of immune responses and facilitation of tumor progression. Interestingly, recent research has highlighted the potential of repolarizing TAMs from an M2 to a pro-inflammatory M1 status-a shift that has shown promise in impeding tumor growth and enhancing immune responsiveness. This concept is particularly intriguing as it offers a new dimension to cancer therapy by targeting the tumor microenvironment, which is a significant departure from traditional approaches that focus solely on tumor cells. However, the clinical application of TAM-modulating agents is often challenged by issues such as insufficient tumor accumulation and off-target effects, limiting their effectiveness and safety. In this regard, nanomaterials have emerged as a novel solution. They serve a dual role: as delivery vehicles that can enhance the accumulation of therapeutic agents in the tumor site and as TAM-modulators. This dual functionality of nanomaterials is a significant advancement as it addresses the key limitations of current TAM-modulating strategies and opens up new avenues for more efficient and targeted therapies. This review provides a comprehensive overview of the latest mechanisms and strategies involving nanomaterials in modulating macrophage polarization within the TME. It delves into the intricate interactions between nanomaterials and macrophages, elucidating how these interactions can be exploited to drive macrophage polarization towards a phenotype that is more conducive to anti-tumor immunity. Additionally, the review explores the burgeoning field of TAM-associated nanomedicines in combination with tumor immunotherapy. This combination approach is particularly promising as it leverages the strengths of both nanomedicine and immunotherapy, potentially leading to synergistic effects in combating cancer.

The synergistic immunotherapeutic impact of engineered CAR-T cells with PD-1 blockade in lymphomas and solid tumors: a systematic review

Currently, therapies such as chimeric antigen receptor-T Cell (CAR-T) and immune checkpoint inhibitors like programmed cell death protein-1 (PD-1) blockers are showing promising results for numerous cancer patients. However, significant advancements are required before CAR-T therapies become readily available as off-the-shelf treatments, particularly for solid tumors and lymphomas. In this review, we have systematically analyzed the combination therapy involving engineered CAR-T cells and anti PD-1 agents. This approach aims at overcoming the limitations of current treatments and offers potential advantages such as enhanced tumor inhibition, alleviated T-cell exhaustion, heightened T-cell activation, and minimized toxicity. The integration of CAR-T therapy, which targets tumor-associated antigens, with PD-1 blockade augments T-cell function and mitigates immune suppression within the tumor microenvironment. To assess the impact of combination therapy on various tumors and lymphomas, we categorized them based on six major tumor-associated antigens: mesothelin, disialoganglioside GD-2, CD-19, CD-22, CD-133, and CD-30, which are present in different tumor types. We evaluated the efficacy, complete and partial responses, and progression-free survival in both pre-clinical and clinical models. Additionally, we discussed potential implications, including the feasibility of combination immunotherapies, emphasizing the importance of ongoing research to optimize treatment strategies and improve outcomes for cancer patients. Overall, we believe combining CAR-T therapy with PD-1 blockade holds promise for the next generation of cancer immunotherapy.

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

Dual-drug controllable co-assembly nanosystem for targeted and synergistic treatment of hepatocellular carcinoma

The effectiveness of chemotherapeutic agents for hepatocellular carcinoma (HCC) is unsatisfactory because of tumor heterogeneity, multidrug resistance, and poor target accumulation. Therefore, multimodality-treatment with accurate drug delivery has become increasingly popular. Herein, a cell penetrating peptide-aptamer dual modified-nanocomposite (USILA NPs) was successfully constructed by coating a cell penetrating peptide and aptamer onto the surface of sorafenib (Sora), ursolic acid (UA) and indocyanine green (ICG) condensed nanodrug (USI NPs) via one-pot assembly for targeted and synergistic HCC treatment. USILA NPs showed higher cellular uptake and cytotoxicity in HepG2 and H22 cells, with a high expression of epithelial cell adhesion molecule (EpCAM). Furthermore, these NPs caused more significant mitochondrial membrane potential reduction and cell apoptosis. These NPs could selectively accumulate at the tumor site of H22 tumor-bearing mice and were detected with the help of ICG fluorescence; moreover, they retarded tumor growth better than monotherapy. Thus, USILA NPs can realize the targeted delivery of dual drugs and the integration of diagnosis and treatment. Moreover, the effects were more significant after co-administration of iRGD peptide, a tumor-penetrating peptide with better penetration promoting ability or programmed cell death ligand 1 (PD-L1) antibody for the reversal of the immunosuppressive state in the tumor microenvironment. The tumor inhibition rates of USILA NPs + iRGD peptide or USILA NPs + PD-L1 antibody with good therapeutic safety were 72.38 % and 67.91 % compared with control, respectively. Overall, this composite nanosystem could act as a promising targeted tool and provide an effective intervention strategy for enhanced HCC synergistic treatment.

Key oncogenic signaling pathways affecting tumor-infiltrating lymphocytes infiltration in hepatocellular carcinoma: basic principles and recent advances

The incidence of hepatocellular carcinoma (HCC) ranks first among primary liver cancers, and its mortality rate exhibits a consistent annual increase. The treatment of HCC has witnessed a significant surge in recent years, with the emergence of targeted immune therapy as an adjunct to early surgical resection. Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TIL) has shown promising results in other types of solid tumors. This article aims to provide a comprehensive overview of the intricate interactions between different types of TILs and their impact on HCC, elucidate strategies for targeting neoantigens through TILs, and address the challenges encountered in TIL therapies along with potential solutions. Furthermore, this article specifically examines the impact of oncogenic signaling pathways activation within the HCC tumor microenvironment on the infiltration dynamics of TILs. Additionally, a concise overview is provided regarding TIL preparation techniques and an update on clinical trials investigating TIL-based immunotherapy in solid tumors.

Advancing Cancer Immunotherapy: The Potential of mRNA Vaccines As a Promising Therapeutic Approach

mRNA vaccines have long been recognized for their ability to induce robust immune responses. The discovery that mRNA vaccines may also contribute to antitumor immunity has made them a promising therapeutic approach against cancer. Recent advances in understanding of immune system are precious in developing therapeutic strategies that target pathways involved in tumor survival and progression, leading to the most reliable therapeutic strategies in cancer treatment history. Among all traditional cancer treatments, cancer immunotherapies are less toxic and more effective, even in advanced or recurrent stages of cancer. Recent advancements in genomics and machine learning algorithms give new insight into vaccine development. mRNA vaccines are designed to interfere with stimulator of interferon genes (STING) and tumor‐infiltrating lymphocytes pathways, activating more CD8+ T‐cells involved in destroying tumor cells and inhibiting tumor growth. A stronger immune response can be achieved by incorporating immunological adjuvants alongside mRNA. Nonformulated or vehicle‐based mRNA vaccines, when combined with adjuvants, efficiently express tumor antigens through antigen‐presenting cells and stimulate both innate and adaptive immune responses. Codelivery with additional immunotherapeutic agents, such as checkpoint inhibitors, further enhances the efficacy of mRNA vaccines. This article focuses on the current clinical approaches and challenges to consider when developing mRNA‐based vaccine technology for cancer treatment.

Bioinformatic analysis reveals an association between Metadherin with breast cancer prognosis and tumor immune infiltration

Breast cancer metastasis and invasion are both promoted by the oncoprotein Metadherin (MTDH). However, the the role of Metadherin in breast cancer progression and its role in the immune microenvironment. Are not clear. A bioinformatic analysis was performed to demonstrate the prognostic value of Metadherin in BC. In the present study, we found that Metadherin is overexpressed in BC and is significantly correlated with individual cancer stage, age, subclasses, menopause and nodal metastasis status. Metadherin overexpression was associated with a significant decrease in OS and DSS. Cox multivariate analysis indicated that Metadherin was an independent negative prognostic indicator for OS and DSS. Moreover, Metadherin hypomethylation status was associated with poor prognosis. A negative correlation was also noted between Metadherin overexpression and the number of plasmacytoid dendritic cells, cluster of differentiation 8+ T cells, and natural killer cells. Association patterns varied with different subtypes. Various associations between Metadherin levels and immune cell surface markers were revealed. A total of 40 groups of BC and adjacent normal breast tissue samples were collected. Metadherin mRNA was detected by PCR, and its expression levels in BC tissues were significantly increased compared with those noted in normal tissues. The expression levels of Metadherin were also measured in normal and BC cell lines, respectively, and similar conclusions were obtained. The Metadherin mRNA levels were knocked down in SK-BR3 and MDA-MB-231 cell lines and the cell proliferative and migratory activities were determined using Cell Counting Kit-8 and scratch assays, respectively. The results indicated that the cell proliferative and migratory abilities were reduced following knockdown of Metadherin expression. Therefore, Metadherin may be considered as a novel prognostic biomarker in BC.

Clinical significance of preoperative CALLY index for prognostication in patients with esophageal squamous cell carcinoma undergoing surgery

The C-reactive protein-albumin-lymphocyte (CALLY) index has been identified as a useful and sensitive predictive tool for stratification in cancers. This investigation aimed to validate the prognostic ability of CALLY in esophageal squamous cell carcinoma (ESCC). Clinical characteristics of 318 patients with ESCC who underwent radical excision were gathered and analyzed retrospectively. A restricted cubic spline (RCS) model was used to determine an ideal threshold of CALLY due to the non-linear relation. To investigate the predictors, Cox hazard regression analysis was used. The recursive partitioning analysis (RPA), a method of risk categorization, was also developed for prognostic prediction. The receiver operating characteristic (ROC) curves and decision curve analysis (DCA) curves were used to distinguish from the traditional TNM stage. Patients were compared by groups according to the optimal threshold of CALLY index, which was depicted by the non-linear relation between the cancer-specific survival (CSS) and CALLY index (P < 0.0001). Compared to those with high CALLY index, patients with low CALLY index experienced significantly worse 5-year CSS (21.8% vs. 62.6%, P < 0.001). At different TNM stages, patients with high CALLY index also had better 5-year CSS (I: P = 0.029; II: P < 0.001; III: P < 0.001) in subgroup analyses. The hazard ratio for CSS was 0.368 and CALLY index was an independent predictive factor (P < 0.001). Using TNM stage and CALLY-based RPA algorithms, a new staging was created. The RPA model considerably outperformed the TNM classification for prognostication using ROC (P < 0.001). The DCA also demonstrated that the new model outperformed the TNM stage with significantly improved accuracy for CSS. The prognostic value of CALLY in ESCC undergoing radical resection was initially determined in this study. CALLY was substantially related to prognosis and might be utilized in conjunction with TNM to evaluate ESCC prior to surgery.

Pretreatment Pan-Immune-Inflammation Value (PIV) in Predicting Therapeutic Response and Clinical Outcomes of Neoadjuvant Immunochemotherapy for Esophageal Squamous Cell Carcinoma

PURPOSE

The pan-immune-inflammation value (PIV), which reflects the balance between the host immune and inflammatory status, is a readily available index for evaluating cancer outcomes. Until now, however, no study has demonstrated the clinical response of PIV to neoadjuvant immunochemotherapy (NICT) in esophageal squamous cell carcinoma (ESCC).

METHODS

This retrospective study included 218 patients with ESCC who underwent NICT. The relationship between PIV and therapeutic response (pathological complete response [PCR]) and clinical outcomes (overall survival [OS] and disease-free survival [DFS]) was examined. Cox proportional, hazard-regression analyses and the Kaplan-Meier method were used for survival analyses. Recursive partitioning analysis (RPA) was used to establish a novel risk stratification model.

RESULTS

Sixty-six patients (30.3%) achieved PCR after NICT. Using PCR as the endpoint of interest, patients were compared in groups based on the optimal threshold. PIV was closely related to PCR (odds ratio [OR] 0.311, 95% confidence interval [CI] 0.140-0.690, P = 0.004). Compared with patients in the low PIV cohort, patients with high PIV had worse 3-year OS (58.7% vs. 83.6%, P < 0.001) and DFS (51.9% vs. 79.1%, P < 0.001). PIV was an independent predictor of OS (hazard ratio [HR] 2.364, 95% CI 1.183-4.724, P = 0.015) and DFS (HR 1.729, 95% CI 1.026-2.913, P = 0.040). Three risk groups with varied DFS and OS were staged by using an RPA method, and the prognostication accuracy was considerably improved.

CONCLUSIONS

Pretreatment PIV can predict the therapeutic efficacy of NICT for ESCC. Because of better prognostic stratification, pretreatment PIV is a novel, sensitive, and effective indicator in ESCC receiving NICT. The prognostic results of PIV need to be verified in additional prospective studies.

Research Progress on the Anticancer Activity of Plant Polysaccharides

Tumor is a serious threat to human health, with extremely high morbidity and mortality rates. However, tumor treatment is challenging, and the development of antitumor drugs has always been a significant research focus. Plant polysaccharides are known to possess various biological activities. They have many pharmacological properties such as immunomodulation, antitumor, antiviral, antioxidative, antithrombotic, and antiradiation effects, reduction of blood pressure and blood sugar levels, and protection from liver injury. Among these effects, the antitumor effect of plant polysaccharides has been widely studied. Plant polysaccharides can inhibit tumor proliferation and growth by inhibiting tumor cell invasion and metastasis, inducing cell apoptosis, affecting the cell cycle, and regulating the tumor microenvironment. They also have the characteristics of safety, high efficiency, and low toxicity, which can alleviate, to a certain extent, the adverse reactions caused by traditional tumor treatment methods such as surgery, radiotherapy, and chemotherapy. Therefore, this paper systematically summarizes the direct antitumor effects of plant polysaccharides, their regulatory effects on the tumor microenvironment, and intervening many common high-incidence tumors in other ways. It also provides data support for the administration of plant polysaccharides in modern tumor drug therapy, enabling the identification of new targets and development of new drugs for tumor therapy.

Exploring the connection between microsatellite instability and inflammatory indicators in cancers

Aim: This study aimed to investigate the association between microsatellite instability (MSI) status and inflammatory indicators in patients with cancer. Patients & methods: A total of 204 patients with various cancer diagnoses, including 102 with MSI-high (MSI-H) and 102 with microsatellite stable tumors, were enrolled. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), C-reactive protein (CRP)-to-albumin ratio and systemic immune-inflammation index were evaluated. Results: In microsatellite stable patients, NLR, LMR, PLR and systemic immune-inflammation index were significantly linked to worse survival in univariate analysis, and having a LMR ≤2.6 negatively affected survival in multivariate analysis, although these indicators did not affect the survival of MSI-H patients. Conclusion: The impact of chronic inflammation on survival varies with MSI status. Further research is needed for targeted therapies in different tumors.

Spatial analysis of NOS2 and COX2 interaction with T-effector cells reveals immunosuppressive landscapes associated with poor outcome in ER- breast cancer patients

Multiple immunosuppressive mechanisms exist in the tumor microenvironment that drive poor outcomes and decrease treatment efficacy. The co-expression of NOS2 and COX2 is a strong predictor of poor prognosis in ER- breast cancer and other malignancies. Together, they generate pro-oncogenic signals that drive metastasis, drug resistance, cancer stemness, and immune suppression. Using an ER- breast cancer patient cohort, we found that the spatial expression patterns of NOS2 and COX2 with CD3+CD8+PD1- T effector (Teff) cells formed a tumor immune landscape that correlated with poor outcome. NOS2 was primarily associated with the tumor-immune interface, whereas COX2 was associated with immune desert regions of the tumor lacking Teff cells. A higher ratio of NOS2 or COX2 to Teff was highly correlated with poor outcomes. Spatial analysis revealed that regional clustering of NOS2 and COX2 was associated with stromal-restricted Teff, while only COX2 was predominant in immune deserts. Examination of other immunosuppressive elements, such as PDL1/PD1, Treg, B7H4, and IDO1, revealed that PDL1/PD1, Treg, and IDO1 were primarily associated with restricted Teff, whereas B7H4 and COX2 were found in tumor immune deserts. Regardless of the survival outcome, other leukocytes, such as CD4 T cells and macrophages, were primarily in stromal lymphoid aggregates. Finally, in a 4T1 model, COX2 inhibition led to a massive cell infiltration, thus validating the hypothesis that COX2 is an essential component of the Teff exclusion process and, thus, tumor evasion. Our study indicates that NOS2/COX2 expression plays a central role in tumor immunosuppression. Our findings indicate that new strategies combining clinically available NOS2/COX2 inhibitors with various forms of immune therapy may open a new avenue for the treatment of aggressive ER-breast cancers.

Advancing the frontiers of adaptive cell therapy: A transformative mechanistic journey from preclinical to clinical settings

Although the concept of using the patient's immune system to combat cancer has been around for a while, it is only in recent times that substantial progress has been achieved in this field. Over the last ten years, there has been a significant advancement in the treatment of cancer through immune checkpoint blockade. This treatment has been approved for multiple types of tumors. Another approach to modifying the immune system to detect tumor cells and fight them off is adaptive cell therapy (ACT). This therapy involves using T cells that have been modified with either T cell receptors (TCR) or chimeric antigen receptors (CAR) to target the tumor cells. ACT has demonstrated encouraging outcomes in different types of tumors, and clinical trials are currently underway worldwide to enhance this form of treatment. This review focuses on the advancements that have been made in ACT from preclinical to clinical settings till now.

The molecular mechanism of actions and clinical utilities of tumor infiltrating lymphocytes in gastrointestinal cancers: a comprehensive review and future prospects toward personalized medicine

Gastrointestinal (GI) cancers remain a significant global health burden, accounting for a substantial number of cases and deaths. Regrettably, the inadequacy of dependable biomarkers hinders the precise forecasting of patient prognosis and the selection of appropriate therapeutic sequencing for individuals with GI cancers, leading to suboptimal outcomes for numerous patients. The intricate interplay between tumor-infiltrating lymphocytes (TILs) and the tumor immune microenvironment (TIME) has been shown to be a pivotal determinant of response to anti-cancer therapy and consequential clinical outcomes across a multitude of cancer types. Therefore, the assessment of TILs has garnered global interest as a promising prognostic biomarker in oncology, with the potential to improve clinical decision-making substantially. Moreover, recent discoveries in immunotherapy have progressively changed the landscape of cancer treatment and significantly prolonged the survival of patients with advanced cancers. Nonetheless, the response rate remains constrained within solid tumor sufferers, even when TIL landscapes appear comparable, which calls for the development of our understanding of cellular and molecular cross-talk between TIME and tumor. Hence, this comprehensive review encapsulates the extant literature elucidating the TILs' underlying molecular pathogenesis, prognostic significance, and their relevance in the realm of immunotherapy for patients afflicted by GI tract cancers. Within this review, we demonstrate that the type, density, and spatial distribution of distinct TIL subpopulations carries pivotal implications for the prediction of anti-cancer treatment responses and patient survival. Furthermore, this review underscores the indispensable role of TILs in modulating therapeutic responses within distinct molecular subtypes, such as those characterized by microsatellite stability or programmed cell death ligand-1 expression in GI tract cancers. The review concludes by outlining future directions in TIL-based personalized medicine, including integrating TIL-based approaches into existing treatment regimens and developing novel therapeutic strategies that exploit the unique properties of TILs and their potential as a promising avenue for personalized cancer treatment.

Implications of different cell death patterns for prognosis and immunity in lung adenocarcinoma

In recent years, lung adenocarcinoma (LUAD) has become a focus of attention due to its low response to treatment, poor prognosis, and lack of reliable indicators to predict the progression or therapeutic effect of LUAD. Different cell death patterns play a crucial role in tumor development and are promising for predicting LUAD prognosis. From the TCGA and GEO databases, we obtained bulk transcriptomes, single-cell transcriptomes, and clinical information. Genes in 15 types of cell death were analyzed for cell death index (CDI) signature establishment. The CDI signature using necroptosis + immunologic cell death-related genes was established in the TCGA cohort with the 1-, 2-, 3-, 4- and 5-year AUC values were 0.772, 0.736, 0.723, 0.795, and 0.743, respectively. The prognosis was significantly better in the low CDI group than in the high CDI group. We also investigated the relationship between the CDI signature and clinical variables, published prognosis biomarkers, immune cell infiltration, functional enrichment pathways, and immunity biomarkers. In vitro assay showed that HNRNPF and FGF2 promoted lung cancer cell proliferation and migration and were also involved in cell death. Therefore, as a robust prognosis biomarker, CDI signatures can screen for patients who might benefit from immunotherapy and improve diagnostic accuracy and LUAD patient outcomes.

Genetically engineered nano-melittin vesicles for multimodal synergetic cancer therapy

Melittin, the principal constituent in bee venom, is an attractive candidate for cancer therapy. However, its clinical applications are limited by hemolysis, nonspecific cytotoxicity, and rapid metabolism. Herein, a novel genetically engineered vesicular antibody-melittin (VAM) drug delivery platform was proposed and validated for targeted cancer combination therapy. VAM generated from the cellular plasma membrane was bio-synthetically fabricated, with the recombinant protein (hGC33 scFv-melittin) being harbored and displayed on the cell membrane. The bioactive and targetable nanomelittin conjugated by hGC33 scFv could be released in an MMP14-responsive manner at tumor sites, which reduced off-target toxicity, especially the hemolytic activity of melittin. Importantly, VAM could be loaded with small-molecule drugs or nanoparticles for combination therapy. Nanomelittin formed pores in membranes and disturbed phospholipid bilayers, which allowed the anticancer agents (i.e., chemotherapeutic drug doxorubicin and sonosensitizer purpurin 18 nanoparticles) co-delivered by VAM to penetrate deeper tumor sites, leading to synergistic therapeutic effects. In particular, the punching effect generated by sonodynamic therapy further improved the immunomodulatory effect of nanomelittin to activate the immune response. Taken together, our findings indicate that clinically translatable VAM-based strategies represent a universal, promising approach to multimodal synergetic cancer therapy.

The Independent Value of Neutrophil to Lymphocyte Ratio in Gouty Arthritis: A Narrative Review

Since the incidence of gouty arthritis (GA) exhibits yearly increases, accurate assessment and early treatment have significant values for improving disease conditions and monitoring prognosis. Neutrophil to lymphocyte ratio (NLR) is a common indicator in blood routine, which has the characteristics of easy access and low cost. In recent years, NLR has been proven to be an effective indicator for guiding the diagnosis, treatment, and prognosis of various diseases. Moreover, NLR has varying degrees of relationship with various inflammatory biomarkers, which can affect and reflect the inflammatory response in the body. This paper reviews the independent value of NLR for GA and its underlying molecular pathological mechanisms, intending to contribute to the further application of NLR.

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

BACKGROUND

Several researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection.

METHODS

The data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC).

RESULTS

The RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication.

CONCLUSION

The present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.

The prognostic and biology of tumour-infiltrating lymphocytes in the immunotherapy of cancer

Tumour immunotherapy has achieved remarkable clinical success in many different types of cancer in the past two decades. The outcome of immune checkpoint inhibitors in cancer patients has been linked to the quality and magnitude of T cell, NK cell, and more recently, B cell within the tumour microenvironment, suggesting that the immune landscape of a tumour is highly connected to patient response and prognosis. It is critical to understanding tumour immune microenvironments for identifying immune modifiers of cancer progression and developing cancer immunotherapies. The infiltration of solid tumours by immune cells with anti-tumour activity is both a strong prognostic factor and a therapeutic goal. Recent approaches and applications of new technologies, especially single-cell mRNA analysis in dissecting tumour microenvironments have brought important insights into the biology of tumour-infiltrating immune cells, revealed a remarkable degree of cellular heterogeneity and distinct patterns of immune response. In this review, we will discuss recent advances in the understanding of tumour infiltrated lymphocytes, their prognostic benefit, and predictive value for immunotherapy.

Advances in the application of computational pathology in diagnosis, immunomicroenvironment recognition, and immunotherapy evaluation of breast cancer: a narrative review

BACKGROUND

Breast cancer (BC) is a prevalent and highly lethal malignancy affecting women worldwide. Immunotherapy has emerged as a promising therapeutic strategy for BC, offering potential improvements in patient survival. Neoadjuvant therapy (NAT) has also gained significant clinical traction. With the advancement of computer technology, Artificial Intelligence (AI) has been increasingly applied in pathology research, expanding and redefining the scope of the field. This narrative review aims to provide a comprehensive overview of the current literature on the application of computational pathology in BC, specifically focusing on diagnosis, immune microenvironment recognition, and the evaluation of immunotherapy and NAT response.

METHODS

A thorough examination of relevant literature was conducted, focusing on studies investigating the role of computational pathology in BC diagnosis, immune microenvironment recognition, and immunotherapy and NAT assessment.

RESULTS

The application of computational pathology has shown significant potential in BC management. AI-based techniques enable improved diagnosis and classification of BC subtypes, enhance the identification and characterization of the immune microenvironment, and facilitate the evaluation of immunotherapy and NAT response. However, challenges related to data quality, standardization, and algorithm development still need to be addressed.

CONCLUSION

The integration of computational pathology and AI has transformative implications for BC patient care. By leveraging AI-based technologies, clinicians can make more informed decisions in diagnosis, treatment planning, and therapeutic response assessment. Future research should focus on refining AI algorithms, addressing technical challenges, and conducting large-scale clinical validation studies to facilitate the translation of computational pathology into routine clinical practice for BC patients.

High Tumor-Infiltrating Lymphocyte Count Is Associated with Distinct Gene Expression Profile and Longer Patient Survival in Advanced Ovarian Cancer

Cancer-related immunity plays a significant role in the outcome of ovarian cancer, but the exact mechanisms are not fully explored. A retrospective, real-life observational study was conducted including 57 advanced ovarian cancer patients. Immunohistochemistry for CD4+, CD8+, and CD45+ was used for assessing tumor-infiltrating immune cells. Furthermore, an immune-related gene expression assay was performed on 12-10 samples from patients with less than and more than 1-year overall survival (OS), respectively. A higher number of CD4+ (p = 0.0028) and CD45+ (p = 0.0221) immune cells within the tumor microenvironment were associated with longer OS of patients. In a multivariate setting, higher CD4+ T cell infiltration predicted longer OS (p = 0.0392). Twenty-three differentially expressed genes-involved in antigen presentation, costimulatory signaling, matrix remodeling, metastasis formation, and myeloid cell activity-were found when comparing the prognostic groups. It was found that tumor-infiltrating immune cell counts are associated with peculiar gene expression patterns and bear prognostic information in ovarian cancer. SOX11 expression emerged and was validated as a predictive marker for OS.

Immunotherapy and immunoevasion of colorectal cancer

The tremendous success of immunotherapy in clinical trials has led to its establishment as a new pillar of cancer therapy. However, little clinical efficacy has been achieved in microsatellite stable colorectal cancer (MSS-CRC), which constitutes most CRC tumors. Here, we discuss the molecular and genetic heterogeneity of CRC. We review the immune escape mechanisms, and focus on the latest advances in immunotherapy as a treatment modality for CRC. By providing a better understanding of the tumor microenvironment (TME) and the molecular mechanisms underlying immunoevasion, this review offers an insight into developing therapeutic strategies that are effective for patients with various subsets of CRC.

Proteomic Profiling and Tumor Microenvironment Characterization Reveal Molecular and Immunological Hallmarks of Left-Sided and Right-Sided Colon Cancer Tumorigenesis

Left-sided and right-sided colon cancer (LSCC and RSCC) display different biological and clinical characteristics. However, the differences in their tumorigenesis and tumor microenvironment remain unclear. In this study, we profiled the proteomic landscapes of LSCC and RSCC with data-independent acquisition mass spectrometry (DIA-MS) using fresh tumor and adjacent normal tissues from 24 patients. A total of 7403 proteingroups were primarily identified with DIA-MS. After quality control, 7212 proteingroups were used for further analysis. Through comparing the difference in proteomic profiles between LSCC and RSCC samples, 2556 commonly and 1982 region-type-specific regulated proteingroups were characterized. During the development of LSCC and RSCC, metabolic, growth, cell division, cell adhesion, and migration pathways were found to be significantly dysregulated (P < 0.05), which was further confirmed by transcriptome data from TCGA. Compared to RSCC, most parts of the immune-related signatures, immune cell infiltration scores, and overall immune scores of LSCC were higher. The systematic elucidation of proteomic and transcriptomic profiles in this work improves our understanding of tumorigenesis and immune microenvironment characteristics of LSCC and RSCC.

Platelet-Lymphocyte and Neutrophil-Lymphocyte Ratios Are Prognostic Markers for Pheochromocytomas and Paragangliomas

CONTEXT

Preoperative inflammatory markers, such as the neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR), have recently been proposed as prognostic markers in different tumors. However, their predictive values in patients with pheochromocytomas and paragangliomas (PPGLs) are uncertain.

OBJECTIVE

This study aimed to investigate the prognostic significance of inflammatory biomarkers in PPGL patients.

METHODS

Data from 1247 consecutive PPGL patients between 2002 and 2020 were evaluated. The preoperative inflammatory markers were evaluated. The prognostic roles were identified by X-tile software, Kaplan-Meier curves, and Cox regression models.

RESULTS

A total of 728 patients were included in the analysis, with a median follow-up of 63 months (IQR, 31-111 months); 31 individuals died, 28 patients developed metastases, and 12 patients developed recurrence. Our study showed that deaths were observed significantly more frequently in patients with high NLR(≥3.5) and high PLR (≥217.4) than those with low NLR (<3.5) (P = .003) and low PLR (<217.4) (P = .005). Elevated NLR (≥3.5) and elevated PLR (≥217.4) was significantly associated with decreased overall survival (OS) (P = .005), and elevated PLR (≥238.3) was significantly associated with decreased metastasis-free survival (MFS) (P = .021). Cox models illustrated that NLR and PLR were independent prognostic factors for OS, and PLR was an independent prognostic factor for MFS.

CONCLUSION

Both elevated NLR and PLR are associated with poor prognosis in PPGLs. They are convenient predictive markers that could be used in daily clinical practice.

Targeting tumor microenvironment using tumor-infiltrating lymphocytes as therapeutics against tumorigenesis

The immune system plays a vital role in suppressing tumor cell progression. The tumor microenvironment augmented with significant levels of tumor-infiltrating lymphocytes has been widely investigated and it is suggested that tumor-infiltrating lymphocytes have shown a significant role in the prognosis of cancer patients. Compared to ordinary non-infiltrating lymphocytes, tumor-infiltrating lymphocytes (TILs) are a significant population of lymphocytes that infiltrate tumor tissue and have a higher level of specific immunological reactivity against tumor cells. They serve as an effective immunological defense against various malignancies. TILs are a diverse group of immune cells that are divided into immune subsets based on the pathological and physiological impact they have on the immune system. TILs mainly consist of B-cells, T-cells, or natural killer cells with diverse phenotypic and functional properties. TILs are known to be superior to other immune cells in that they can recognize a wide range of heterogeneous tumor antigens by producing many clones of T cell receptors (TCRs), outperforming treatments like TCR-T cell and CAR-T therapy. With the introduction of genetic engineering technologies, tumor-infiltrating lymphocytes (TILs) have become a ground-breaking therapeutic option for malignancies, but because of the hindrances opposed by the immune microenvironment and the mutation of antigens, the development of TILs as therapeutic has been hindered. By giving some insight into the many variables, such as the various barriers inhibiting its usage as a potential therapeutic agent, we have examined various aspects of TILs in this work.