First-line treatment with KN046, chemotherapy and palliative radiotherapy for advanced esophageal squamous cell carcinoma: an open-label, dose escalation, and dose expansion phase Ib trial.

There is growing evidence to suggest that radiotherapy might enhance the efficacy of immunotherapy. This study aimed to assess the possibility of KN046, a bispecific antibody targeting PD-L1 and CTLA-4, combined with chemotherapy and palliative radiotherapy for advanced esophageal squamous cell carcinoma (ESCC). In this open-label, phase Ib trial, patients with advanced ESCC were administered chemotherapy with palliative radiotherapy, and KN046 in the predefined escalation dosages of 1, 3, or 5 mg/kg (every 3 weeks during chemotherapy cycles and every 2 weeks during KN046 maintenance). The chemotherapy regimen constituted cisplatin (75 mg/m2 i.v., d1) and paclitaxel (135-175 mg/m2 ivgtt., d1). Radiotherapy specifics, including site, timing, dose, and fragmentation pattern, were at the investigator's discretion. The primary outcome was dose-limiting toxicity (DLT). From May 2019 to April 2021, 25 patients were enrolled across the dosage groups: 3 in 1 mg/kg, 12 in 3 mg/kg, and 10 in 5 mg/kg. No DLT was observed during the dose escalation. The objective response rate was 41.7% (95%CI 22.1-63.4), while the disease control rate was 87.5% (95%CI 67.6-97.3). At a median follow-up of 11.8 months, the median progression-free survival was 7.8 months (95%CI 5.2-9.7) and median overall survival was 15.9 months (95%CI 8.4-NE). Serious adverse events were reported in 48.0% of patients, predominantly leukopenia (16%), immune-mediated enterocolitis (12%), immune-mediated pneumonitis (8%), and neutropenia (8%). Combining KN046 with chemotherapy and palliative radiotherapy might be feasible, showing a favorable safety profile and notable efficacy in advanced ESCC patients.

A prognostic nomogram for T3N0M0 esophageal squamous cell carcinoma patients undergoing radical surgery based on computed tomography radiomics and inflammatory nutritional biomarkers.

BACKGROUND: This study explores the significance of computed tomography (CT) radiomic features, along with inflammation and nutrition biomarkers, in the prognosis of postoperative patients with T3N0M0 esophageal squamous cell carcinoma (ESCC). The study aims to construct a related nomogram. METHODS: A total of 114 patients were enrolled and randomly assigned to training and validation cohorts in a 7:3 ratio. Radiomic features were extracted from their preoperative chest-enhanced CT arterial images of the primary tumor, and inflammatory and nutritional indices, including neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), were calculated based on laboratory data from the 3 days before surgery. Intra-class correlations coefficient (ICC) and least absolute shrinkage and selection operator (Lasso) were applied to screen valuable radiomics features predicting overall survival (OS), and the Rad-score was calculated. In the training cohort, univariate and multivariate Cox regression analyses identified independent prognostic factors, which were adopted to establish the nomogram. RESULTS: Eight radiomic features were selected for Rad-score calculation. Multivariate Cox regression revealed Rad-score, PNI, NLR, and PLR as independent prognostic factors for ESCC patients (p < 0.05). A nomogram was constructed based on these variables. The concordance index (C-index) for the nomogram was 0.797 (95% CI: 0.726-0.868) in the training cohort and 0.796 (95% CI: 0.702-0.890) in the validation cohort. Calibration curves indicated good calibration ability, and the receiver operating characteristic (ROC) analysis demonstrated superior discriminative ability for the nomogram in comparison to the Rad-score alone. Decision curve analysis (DCA) confirmed the clinical utility of the nomogram. CONCLUSION: We developed and validated a nomogram for predicting the OS of postoperative T3N0M0 ESCC patients, integrating nutritional, inflammatory markers, and radiomic signature. The combined nomogram can serve as a robust tool for risk stratification and clinical management.

Pilot study of a novel nanobody 68 Ga-NODAGA-SNA006 for instant PET imaging of CD8+ T cells.

PURPOSE: Positron emission tomography (PET) with specific diagnostic probes for quantifying CD8+ T cells has emerged as a powerful technique for monitoring the immune response. However, most CD8+ T cell radiotracers are based on antibodies or antibody fragments, which are slowly cleared from circulation. Herein, we aimed to develop and assess 68 Ga-NODAGA-SNA006 for instant PET (iPET) imaging of CD8+ T cells. METHODS: A novel nanobody without a hexahistidine (His6) tag, SNA006-GSC, was designed, site-specifically conjugated with NODAGA-maleimide and radiolabelled with 68 Ga. The PET imaging profiles of 68 Ga-NODAGA-SNA006 were evaluated in BALB/c MC38-CD8+/CD8- tumour models and cynomolgus monkeys. Three volunteers with lung cancer underwent whole-body PET/CT imaging after 68 Ga-NODAGA-SNA006 administration. The biodistribution, pharmacokinetics and dosimetry of patients were also investigated. In addition, combined with immunohistochemistry (IHC), the quantitative performance of the tracer for monitoring CD8 expression was evaluated in BALB/c MC38-CD8+/CD8- and human subjects. RESULTS: 68 Ga-NODAGA-SNA006 was prepared with RCP > 98% and SA > 100 GBq/µmol. 68 Ga-NODAGA-SNA006 exhibited specific uptake in MC38-CD8+ xenografts tumours, CD8-rich tissues (such as the spleen) in monkeys and CD8+ tumour lesions in patients within 1 h. Fast washout from circulation was observed in three volunteers (t1/2 < 20 min). A preliminary quantitative linear relationship (R2 = 0.9668, p < 0.0001 for xenografts and R2 = 0.7924, p = 0.0013 for lung patients) appeared between 68 Ga-NODAGA-SNA006 uptake and CD8 expression. 68 Ga-NODAGA-SNA006 was well tolerated by all patients. CONCLUSION: 68 Ga-NODAGA-SNA006 PET imaging can instantly quantify CD8 expression with an ideal safety profile and is expected to be important for dynamically tracking CD8+ T cells and monitoring immune responses for individualised cancer immunotherapy. TRIAL REGISTRATION: NCT05126927 (19 November 2021, retrospectively registered).

Lentinan enhances the antitumor effects of Delta-like 1 via neutrophils.

BACKGROUND: Selective activation of Delta-like 1 (DLL1)-Notch signaling is a new approach to activate CD8+ T cell and suppress tumor growth, while the efficacy remains modest. Lentinan (LNT) is a clinically used immunomodulation agent. Thus, we hypothesized that LNT could improve the efficacy of DLL1. METHODS: The effects of LNT combined with DLL1 on tumor growth were evaluated by growth curve and tumor weight in EO771 breast and LAP0297 lung tumor models. The impacts on immune cells and gene expression in tumor tissues were determined by flow cytometry, qPCR. Neutrophil depletion was used to investigate the mechanism of the combination therapy on tumor growth. The data sets were compared using unpaired student's t-test or ordinary one-way ANOVA. RESULTS:  LNT treatments additively improved the antitumor effects of DLL1 in EO771 breast tumor growth. Remarkably, LNT treatments synergistically enhanced the suppression of DLL1 on LAP0297 lung tumor growth, resulting in tumor regression. Mechanically, the combination of LNT and DLL1 interventions not only promoted the accumulation and activation of CD8+ T cells, but also increased intratumoral CD45+CD11b+Ly6G+ neutrophils. Reduced neutrophils by anti-Gr1 antibody administrations reversed the improved antitumor effects by LNT treatments in LAP0297 lung tumor. These results suggest that LNT treatments improve the inhibition of DLL1 on tumor growth via neutrophils. CONCLUSIONS: Our findings indicates that LNT and DLL1 may induce synergistical antitumor immunity via simultaneous modulating lymphoid and myeloid cell populations regardless of the type of tumor, providing a potential new strategy to potentiate cancer immunotherapy.

Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.

OBJECTIVES: Accurate contouring of the clinical target volume (CTV) is a key element of radiotherapy in cervical cancer. We validated a novel deep learning (DL)-based auto-segmentation algorithm for CTVs in cervical cancer called the three-channel adaptive auto-segmentation network (TCAS). METHODS: A total of 107 cases were collected and contoured by senior radiation oncologists (ROs). Each case consisted of the following: (1) contrast-enhanced CT scan for positioning, (2) the related CTV, (3) multiple plain CT scans during treatment and (4) the related CTV. After registration between (1) and (3) for the same patient, the aligned image and CTV were generated. Method 1 is rigid registration, method 2 is deformable registration, and the aligned CTV is seen as the result. Method 3 is rigid registration and TCAS, method 4 is deformable registration and TCAS, and the result is generated by a DL-based method. RESULTS: From the 107 cases, 15 pairs were selected as the test set. The dice similarity coefficient (DSC) of method 1 was 0.8155 ± 0.0368; the DSC of method 2 was 0.8277 ± 0.0315; the DSCs of method 3 and 4 were 0.8914 ± 0.0294 and 0.8921 ± 0.0231, respectively. The mean surface distance and Hausdorff distance of methods 3 and 4 were markedly better than those of method 1 and 2. CONCLUSIONS: The TCAS achieved comparable accuracy to the manual delineation performed by senior ROs and was significantly better than direct registration.

Tumor-associated macrophages promote the metastasis and growth of non-small-cell lung cancer cells through NF-κB/PP2Ac-positive feedback loop.

Non-small-cell lung cancer (NSCLC), with its aggressive biological behavior, is one of the most diagnosed cancers. Tumor-associated inflammatory cells play important roles in the interaction between chronic inflammation and lung cancer, however the mechanisms involved are far from defined. In the present study, by developing an orthotopic NSCLC mouse model based on chronic inflammation, we proved that an inflammatory microenvironment accelerated the growth of orthotopic xenografts in vivo. Tumor-associated macrophages, the most abundant population of inflammatory cells, were identified. Treatment with macrophage-conditioned medium (MCM) promoted the growth and migration of NSCLC cells. Using bioinformatics analysis, we identified downregulated PP2Ac expression in NSCLC cells upon treatment with MCM. We further confirmed that this downregulation was executed in an NF-κB pathway-dependent manner. As IκB kinase (IKK) has been proved to be a substrate of PP2Ac, inhibition on PP2Ac could result in amplification of NF-κB pathway signaling. Overexpression of PP2Ac, or the dominant-negative forms of IKK or IκB, attenuated the acceleration of growth and metastasis by MCM. Using bioinformatics analysis, we further identified that CXCL1 and COL6A1 could be downstream of NF-κB/PP2Ac pathway. Luciferase assay and ChIP assay further confirmed the location of response elements on the promoter regions of CXCL1 and COL6A1. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted proliferation and migration.

CTLA4 blockade promotes vessel normalization in breast tumors via the accumulation of eosinophils.

Immune checkpoint blockade (ICB) has shown long-term survival benefits, but only in a small fraction of cancer patients. Recent studies suggest that improved vessel perfusion by ICB positively correlates with its therapeutic outcomes. However, the underlying mechanism of such a process remains unclear. Here, we show that anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA4) treatment-induced tumor vessel normalization was accompanied by an increased infiltration of eosinophils into breast tumors. Eosinophil accumulation was positively correlated with the responsiveness of a breast tumor to anti-CTLA4 therapy. Depletion of eosinophils subsequently negated vessel normalization, reduced antitumor immunity and attenuated tumor growth inhibition by anti-CTLA4 therapy. Moreover, intratumoral accumulation of eosinophils relied on T lymphocytes and interferon γ production. Together, these results suggest that eosinophils partially mediate the antitumor effects of CTLA4 blockade through vascular remodeling. Our findings uncover an unidentified role of eosinophils in anti-CTLA4 therapy, providing a potential new target to improve ICB therapy and to predict its efficacy.

Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma.

Objective: Cancer stem cells are self-renewal cells in tumors and can produce heterogeneous tumor cells, which play an important role in the development of lung squamous cell carcinoma (LSCC). In our research, we aimed to explore the expression of genes related to LSCC stem cells.Methods: We downloaded the RNAseq data, the pathological and prognostic profiles of LSCC cases from the public database TCGA. The mRNA expression-based stiffness index (mRNAsi) of LSCC was calculated and the prognostic value of mRNAsi was discussed. Then, we constructed a weighted gene co-expression network analysis (WGCNA) to screen key genes related to mRNAsi of LSCC.Results: MRNAsi is an independent prognostic factor in LSCC. We screened 5 key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi of LSCC based on WGCNA. The key genes were highly expressed in the tumor samples compared to the normal samples. In addition, there is a strong interaction between proteins of these key genes and a strong co-expression relationship at the transcriptional level.Conclusions: To conclude, mRNAsi play an important role in LSCC. Five key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi were screened, which may act as therapeutic targets for inhibiting the stem cell characteristics of LSCC.

Acylglycerol kinase promotes the stemness of nasopharyngeal carcinoma cells by promoting ß-catenin translocation to the nucleus through activating PI3K/Akt pathway.

Recent evidences show that acylglycerol kinase (AGK) expression is related to the occurrence and development of various human cancers. However, its roles in nasopharyngeal carcinoma (NPC) progression are still unclear. This work aims to explore the roles of AGK in NPC cell stemness. It was shown that AGK expression was higher in NPC tissues compared to the adjacent tissues. Online dataset analysis revealed that AGK expression was negatively correlated with the overall survival of NPC patients. Gain and loss of functional experiments demonstrated that AGK positively regulated the stemness of NPC cells, as evident by the change of the tumor sphere-formation ability, ALDH1 activity and expression of stemness critical regulators. KEGG analysis were performed to determine the potential pathways of AGK involved in NPC cell stemness and showed that the PI3K/Akt pathway exhibited the most correlation with AGK expression. Further mechanistic studies confirmed that AGK promoted the stemness of NPC cells through activating the PI3K/Akt pathway, and thus enhancing ß-catenin accumulation in nucleus. This study demonstrates a novel AGK/PI3K/Akt/ß-catenin axis involving in NPC cell stemness.

IMRT combined with S-1 concurrent chemoradiotherapy in locally advanced nasopharyngeal carcinoma: a prospective phase II study.

Purpose The current standard treatment for locally advanced nasopharyngeal carcinoma (LANPC) is intensity-modulated radiation therapy (IMRT) plus cisplatin concurrent chemoradiotherapy (CCRT). However, this regimen has well-known hematological and gastrointestinal toxicities. Many studies have reported that S-1 was effective in the treatment of multiple solid cancers with mild toxicities. However, knowledge regarding IMRT plus S-1 CCRT in LANPC is lacking. Therefore, we conducted this prospective phase II trial to evaluate the efficacy and safety of this regimen in LANPC. Patients and Methods Eligible patients with histologically confirmed LANPC were enrolled in this study. IMRT was given in 30-32 fractions five times per week. Concurrently, S-1 was administrated twice per day orally based on the body surface area (BSA < 1.25 m2, 30 mg; BSA: 1.25-1.5 m2, 40 mg; BSA > 1.5 m2, 50 mg). The primary endpoints were progression-free survival (PFS) and adverse events. Results From August 1, 2013, to December 15, 2017, 131 patients were enrolled in this study. The distribution of disease stages among the patients was as follows: 21 patients were in stage II (16.0%), 42 patients were in stage III (32.0%), and 68 patients were in stage IV (52.0%). After CCRT, the 3-year PFS, overall survival (OS), local recurrence-free survival (LRFS) and distant metastasis-free survival (DMFS) rates were 87.4%, 95.7%, 94.7%, and 91.5%, respectively. The severity of most toxicities was mild. Approximately two-thirds of patients had no hematological toxicity. Grade 2 hematological toxicities included leukopenia (11.5%), anemia (1.5%), and thrombocytopenia (0.8%). Grade 3 hematological toxicities were rarely observed. Conclusion The results demonstrated that IMRT plus S-1 CCRT was effective with mild toxicity for patients with LANPC.

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study.

Preoperative laboratory data indicators significantly affect the prognosis of a variety of tumors. Nevertheless, the combined effect of systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) on overall survival (OS) in patients with esophageal carcinoma remains unclear. Thus, we examined these associations among patients with postoperative staged T3N0M0 esophageal carcinoma. The data of 246 patients with postoperative staged T3N0M0 esophageal carcinoma from January 1, 2010, to December 31, 2022, were retrospectively analyzed. OS was measured from the date of pathological diagnosis until either death or the last follow-up. The Kaplan-Meier method and multivariate Cox regression model were used to analyze the relationship between neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Platelet-to-lymphocyte ratio (LMR), SII, PNI, and OS. The predictive value of SII and PNI as a combined index was analyzed by the receiver operating characteristic curve (ROC). A total of 246 patients aged 65.5 ±â€…7.4 years were included in this study and 181 (73.6%) were male. The univariate analysis revealed that differentiation, vessel involvement, postoperative treatment, NLR, SII, PLR, LMR, PNI were predictors of OS (P < .05). After adjusted for potential confounds, multivariate Cox regression analysis showed that the differentiation, SII, PNI, and postoperative treatment were independent prognostic factors correlated with OS in patients with postoperative staged T3N0M0 esophageal carcinoma (P < .05). SII and PNI, as a combined indicator, have a higher predictive value for OS. The NLR, SII, PLR, LMR, and PNI could all be used as independent predictors of OS in patients with postoperative staged T3N0M0 esophageal carcinoma. The combination of SII and PNI can significantly improve the accuracy of prediction.

Differentially expressed microRNA in prognosis of gastric cancer with Lauren classification.

BACKGROUND: Gastric cancer (GC) is one of the most common tumors. There were several classifications of GC recently. The value of Lauren classification in evaluating the prognosis after radical gastrectomy was still unclear and the prognosis of gastric cancer remained relatively poor in the absence of prognostic biomarkers. This study aimed to explore microRNA (miRNA) in the prognosis of GC with different Lauren classification. METHODS: A retrospective study of 1144 patients was performed in this study. Quantificational reverse transcription-PCR (qRT-PCR) was used to examine the expression of miRNAs. Univariate and multivariate analysis were performed to evaluate prognosis value of Lauren classification. RESULTS: Total 1144 GC patients were recruited in this cohort, including 302 diffuse type (26.4%), 436 intestinal type (38.1%) and 406 mixed type (35.5%) GC. Multivariate analysis showed that Lauren classification, patients' age, tumor size, tumor infiltrating depth, vascular nerve infiltrating and metastatic lymph nodes ration were significantly correlated with GC patients' OS and DFS. The miR-141-3p, miR-200b-3p and miR-133a-5p were significantly down-regulated in diffuse type compared to intestinal type GC tissues, the miR-105-5p had significant lower expression in diffuse type compared with intestinal type and mixed type GC tissues. As a consequence of univariate analysis, low miR-141-3p in diffuse type GC showed significant worse OS and DFS than high miR-141-3p. CONCLUSIONS: Lauren classification was an independent prognostic factor in GC. MiR-141-3p was an independent prognostic factor and a promising prognostic biomarker in Lauren classification GC.

Radiomics Models Derived From Arterial-Phase-Enhanced CT Reliably Predict Both PD-L1 Expression and Immunotherapy Prognosis in Non-small Cell Lung Cancer: A Retrospective, Multicenter Cohort Study.

RATIONALE AND OBJECTIVES: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC) and programmed cell death-ligand 1 (PD-L1) is a companion biomarker. This study aims to use baseline arterial-phase enhanced CT (APECT) to construct efficient radiomic models for predicting PD-L1 expression and immunotherapy prognosis in NSCLC. MATERIALS AND METHODS: We extracted radiomics features from the baseline APECT images of 204 patients enrolled in a published multicenter clinical trial that commenced on August 23, 2018, and concluded on November 15, 2019 (ClinicalTrials.gov: NCT03607539). Of these patients, 146 patients from selected centers were assigned to the training cohort. The least absolute shrinkage and selection operator (LASSO) method was used to reduce dimensionality of radiomics features and calculate tumor scores. Models were created using naive bayes, decision trees, XGBoost, and random forest algorithms according to tumor scores. These models were then validated in an independent validation cohort comprising 58 patients from the remaining centers. RESULTS: The random forest algorithm outperformed the other methods. In the three-classification scenario, the random forest model achieving the area under the curve (AUC) values of 0.98 and 0.94 in the training and validation cohorts, respectively. In the two-classification scenario, the random forest model achieved AUCs of 0.99 (95%CI: 0.97-1.0, P < 0.0001) and 0.93 (95%CI: 0.83-0.98, P < 0.0001) in the training and validation cohorts, respectively. Furthermore, patients classified as PD-L1 high-expression by this model can predict treatment response (AUC=0.859, 95%CI: 0.7-0.96, P < 0.001) and improved survival (HR=0.2, 95%CI: 0.08-0.53, P = 0.001) only in validation sintilimab arm. CONCLUSION: Radiomics models based on APECT represent a potential non-invasive approach to robustly predict PD-L1 expression and ICI treatment outcomes in patients with NSCLC, which could significantly improve precision cancer immunotherapy.

CDKL3 shapes immunosuppressive tumor microenvironment and initiates autophagy in esophageal cancer.

Background: CDKL3 has been associated with the prognosis of several tumors. However, the potential role of CDKL3 in immunotherapy and the tumor microenvironment (TME) in esophageal carcinoma (ESCA) remains unclear. Methods: In this study, Cox regression analysis was used to assess the predictive value of CDKL3 for ESCA outcomes. We systematically correlated CDKL3 with immunological features in the TME. The role of CDKL3 in predicting the efficacy of immunotherapy was also analyzed. Correlation analysis, Cox analysis and LASSO Cox regression were used to construct the CDKL3-related autophagy (CrA) risk score model. The relationship between CDKL3 expression and postoperative pathological complete response (pCR) rate in esophageal squamous cell carcinoma (ESCC) patients undergoing neoadjuvant chemoradiotherapy (nCRT) was evaluated using Immunohistochemical staining (IHC). The relationship between CDKL3 expression and autophagy induction was confirmed by immunofluorescence staining and western blot, and the effect of CDKL3 expression on macrophage polarization was verified by flow cytometry. Results: High expression of CDKL3 was found in ESCA and was associated with poor prognosis in ESCA. Moreover, CDKL3 expression was negatively correlated with tumor-infiltrating immune cells (TIICs), the integrality of the cancer immunity cycles, and anti-tumor signatures, while CDKL3 expression was positively correlated with suppressive TME-related chemokines and receptors, immune hyperprogressive genes, and suppressive immune checkpoint, resulting in immunosuppressive TME formation in ESCA. An analysis of immunotherapy cohorts of the ESCA and pan-cancer showed a better response to immunotherapy in tumor patients with lower CDKL3 levels. The CrA risk score model was constructed and validated to accurately predict the prognosis of ESCA. Notably, the CrA risk score of ESCA patients was significantly positively correlated with M2 macrophages. Furthermore, knockdown CDKL3 in KYSE150 cells could inhibit autophagy induction and M2 macrophage polarization. And, radiation could downregulate CDKL3 expression and autophagy induction, while ESCC patients with high CDKL3 expression had a significantly lower response rate after nCRT than those with low CDKL3 expression. Conclusion: CDKL3 may play an important role in anti-tumor immunity by regulating autophagy to promote the formation of immunosuppressive TME, thus playing a critical role in the prognosis of ESCA.

Identification and validation of a novel risk model based on cuproptosis­associated m6A for head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a prevalent cancer with a poor survival rate due to anatomical limitations of the head and a lack of reliable biomarkers. Cuproptosis represents a novel cellular regulated death pathway, and N6-methyladenosine (m6A) is the most common internal RNA modification in mRNA. They are intricately connected to tumor formation, progression, and prognosis. This study aimed to construct a risk model for HNSCC using a set of mRNAs associated with m6A regulators and cuproptosis genes (mcrmRNA). METHODS: RNA-seq and clinical data of HNSCC patients from The Cancer Genome Atlas (TCGA) database were analyzed to develop a risk model through the least absolute shrinkage and selection operator (LASSO) analysis. Survival analysis and receiver operating characteristic (ROC) analysis were performed for the high- and low-risk groups. Additionally, the model was validated using the GSE41613 dataset from the Gene Expression Omnibus (GEO) database. GSEA and CIBERSORT were applied to investigate the immune microenvironment of HNSCC. RESULTS: A risk model consisting of 32 mcrmRNA was developed using the LASSO analysis. The risk score of patients was confirmed to be an independent prognostic indicator by multivariate Cox analysis. The high-risk group exhibited a higher tumor mutation burden. Additionally, CIBERSORT analysis indicated varying levels of immune cell infiltration between the two groups. Significant disparities in drug sensitivity to common medications were also observed. Enrichment analysis further unveiled significant differences in metabolic pathways and RNA processing between the two groups. CONCLUSIONS: Our risk model can predict outcomes for HNSCC patients and offers valuable insights for personalized therapeutic approaches.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer.

BACKGROUND: Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide. Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer (LARC). Except for pathological examination after resection, it is not known exactly whether LARC patients have achieved pathological complete response (pCR) before surgery. To date, there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes. AIM: To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC. METHODS: Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed. Patients were categorized into pCR and non-pCR groups. Univariate analysis (using the χ 2 test or Fisher's exact test) and logistic multivariate regression analysis were used to study clinical predictors affecting pCR. The 5-year disease-free survival (DFS) and overall survival (OS) rates were calculated using Kaplan-Meier analysis, and differences in survival curves were assessed with the log-rank test. RESULTS: Univariate analysis showed that pretreatment carcinoembryonic antigen (CEA) level, lymphocyte-monocyte ratio (LMR), time interval between neoadjuvant therapy completion and total mesorectal excision, and tumor size were correlated with pCR. Multivariate results showed that CEA ≤ 5 ng/mL (P = 0.039), LMR > 2.73 (P = 0.023), and time interval > 10 wk (P = 0.039) were independent predictors for pCR. Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates (94.7% vs 59.7%, P = 0.002) and 5-year OS rates (95.8% vs 80.1%, P = 0.019) compared to the non-pCR group. Tumor deposits (TDs) were significantly correlated with shorter DFS (P = 0.002) and OS (P < 0.001). CONCLUSION: Pretreatment CEA, LMR, and time interval contribute to predicting nCRT efficacy in LARC patients. Achieving pCR demonstrates longer DFS and OS. TDs correlate with poor prognosis.

Multileaf Collimator Modeling and Commissioning for Complex Radiation Treatment Plans Using 2-Dimensional (2D) Diode Array MapCHECK2.

Purpose: This study aims to develop a data-collecting package ExpressMLC and investigate the applicability of MapCHECK2 for multileaf collimator (MLC) modeling and commissioning for complex radiation treatment plans. Materials and methods: The MLC model incorporates realistic parameters to account for sophisticated MLC features. A set of 8 single-beam plans, denoted by ExpressMLC, is created for the determination of parameters. For the commissioning of the MLC model, 4 intensity modulated radiation therapy (IMRT) plans specified by the AAPM TG 119 report were transferred to a computed tomography study of MapCHECK2, recalculated, and compared to measurements on a Varian accelerator. Both per-beam and composite-beam dose verification were conducted. Results: Through sufficient characterization of the MLC model, under 3%/2 mm and 2%/2 mm criteria, MapCHECK2 can be used to accurately verify per beam dose with gamma passing rate better than 90.9% and 89.3%, respectively, while the Gafchromic EBT3 films can achieve gamma passing rate better than 89.3% and 85.7%, respectively. Under the same criteria, MapCHECK2 can achieve composite beam dose verification with a gamma passing rate better than 95.9% and 90.3%, while the Gafchromic EBT3 films can achieve a gamma passing rate better than 96.1% and 91.8%; the p-value from the Mann Whitney test between gamma passing rates of the per beam dose verification using full MapCHECK2 package calibrated MLC model and film calibrated MLC model is .44 and .47, respectively; the p-value between those of the true composite beam dose verification is .62 and .36, respectively. Conclusion: It is confirmed that the 2-dimensional (2D) diode array MapCHECK2 can be used for data collection for MLC modeling with the combination of the ExpressMLC package of plans, whose doses are sufficient for the determination of MLC parameters. It could be a fitting alternative to films to boost the efficiency of MLC modeling and commissioning without sacrificing accuracy.

CT-based radiomics nomogram for overall survival prediction in patients with cervical cancer treated with concurrent chemoradiotherapy.

Background and purpose: To establish and validate a hybrid radiomics model to predict overall survival in cervical cancer patients receiving concurrent chemoradiotherapy (CCRT). Methods: We retrospectively collected 367 cervical cancer patients receiving chemoradiotherapy from the First Affiliated Hospital of Soochow University in China and divided them into a training set and a test set in a ratio of 7:3. Handcrafted and deep learning (DL)-based radiomics features were extracted from the contrast-enhanced computed tomography (CT), and the two types of radiomics signatures were calculated based on the features selected using the least absolute shrinkage and selection operator (LASSO) Cox regression. A hybrid radiomics nomogram was constructed by integrating independent clinical risk factors, handcrafted radiomics signature, and DL-based radiomics signature in the training set and was validated in the test set. Results: The hybrid radiomics nomogram exhibited favorable performance in predicting overall survival, with areas under the receiver operating characteristic curve (AUCs) for 1, 3, and 5 years in the training set of 0.833, 0.777, and 0.871, respectively, and in the test set of 0.811, 0.713, and 0.730, respectively. Furthermore, the hybrid radiomics nomogram outperformed the single clinical model, handcrafted radiomics signature, and DL-based radiomics signature in both the training (C-index: 0.793) and test sets (C-index: 0.721). The calibration curves and decision curve analysis (DCA) indicated that our hybrid nomogram had good calibration and clinical benefits. Finally, our hybrid nomogram demonstrated value in stratifying patients into high- and low-risk groups (cutoff value: 5.6). Conclusion: A high-performance hybrid radiomics model based on pre-radiotherapy CT was established, presenting strengths in risk stratification.

Vascular Normalization Was Associated with Colorectal Tumor Regression upon Anti-PD-L1 Combinational Therapy.

Anti-PD-L1 therapy exhibits durable efficacy, but only in a small fraction of cancer patients. The immunosuppressive tumor microenvironment (TME) is a crucial obstacle that impedes cancer immunotherapy. Here, we found that anti-PD-L1 therapy coupled with CD4+ T cell depletion induced colorectal tumor regression and vascular normalization, while monotherapy only retarded tumor growth without affecting the tumor vasculature. Moreover, simultaneous PD-L1 blockade and CD4+ T cell depletion eradicated intratumoral PD-L1+ lymphoid and myeloid cell populations, while additively elevating the proportions of CD44+CD69+CD8+, central memory CD44+CD62L+CD8+, and effector memory CD44+CD62L-CD8+ T cells, suggesting a reduction in immunosuppressive cell populations and the activation of CD8+ T cells in the TME. Moreover, anti-PD-L1 therapy reduced the proportions of intratumoral PD-L1+ immune cells and suppressed tumor growth in a CD8+ T cell dependent manner. Together, these results suggest that anti-PD-L1 therapy induces tumor vascular normalization and colorectal tumor regression via CD8+ T cells, which is antagonized by CD4+ T cells. Our findings unveil the positive correlation of tumor regression and vascular normalization in colorectal tumor models upon anti-PD-L1 therapy, providing a potential new strategy to improve its efficacy.

Establishment of a prediction model for severe acute radiation enteritis associated with cervical cancer radiotherapy.

BACKGROUND: Cervical cancer is one of the most common gynecological malignant tumors. Radiation enteritis (RE) leads to radiotherapy intolerance or termination of radiotherapy, which negatively impacts the therapeutic effect and seriously affects the quality of life of patients. If the incidence of RE in patients can be predicted in advance, and targeted clinical preventive treatment can be carried out, the side effects of radiotherapy in cervical cancer patients can be significantly reduced. Furthermore, accurate prediction of RE is essential for the selection of individualized radiation dose and the optimization of the radiotherapy plan. AIM: To analyze the relationships between severe acute RE (SARE) of cervical cancer radiotherapy and clinical factors and dose-volume parameters retrospectively. METHODS: We included 50 cervical cancer patients who received volumetric modulated arc therapy (VMAT) from September 2017 to June 2018 in the Department of Radiotherapy at The First Affiliated Hospital Soochow University. Clinical and dose-volume histogram factors of patients were collected. Logistic regression analysis was used to evaluate the predictive value of each factor for SARE. A nomogram to predict SARE was developed (SARE scoring system ≥ 3 points) based on the multiple regression coefficients; validity was verified by an internal verification method. RESULTS: Gastrointestinal and hematological toxicity of cervical cancer VMAT gradually increased with radiotherapy and reached the peak at the end of radiotherapy. The main adverse reactions were diarrhea, abdominal pain, colitis, anal swelling, and blood in the stool. There was no significant difference in the incidence of gastrointestinal toxicity between the radical and postoperative adjuvant radiotherapy groups (P > 0.05). There were significant differences in the small intestine V20, V30, V40, and rectal V40 between adjuvant radiotherapy and radical radiotherapy after surgery (P < 0.05). Univariate and multivariate analyses revealed anal bulge rating (OR: 14.779, 95%CI: 1.281-170.547, P = 0.031) and disease activity index (DAI) score (OR: 53.928, 95%CI: 3.822-760.948, P = 0.003) as independent predictors of SARE. CONCLUSION: Anal bulge rating (> 0.500 grade) and DAI score (> 2.165 points) can predict SARE. The nomogram shows potential value in clinical practice.