Unlocking Clinical Insights: Lymphocyte-Specific Protein Tyrosine Kinase Candidates as Promising Therapeutic Targets for Pancreatic Cancer Risk Stratification.

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer. Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined. Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis. Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Nanoformulation of dasatinib cannot overcome therapy resistance of pancreatic cancer cells with low LYN kinase expression.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most difficult to treat tumors. The Src (sarcoma) inhibitor dasatinib (DASA) has shown promising efficacy in preclinical studies of PDAC. However, clinical confirmation could not be achieved. Overall, our aim was to deliver arguments for the possible reinitiating clinical testing of this compound in a biomarker-stratifying therapy trial for PDAC patients. We tested if the nanofunctionalization of DASA can increase the drug efficacy and whether certain Src members can function as clinical predictive biomarkers. METHODS: Methods include manufacturing of poly(vinyl alcohol) stabilized gold nanoparticles and their drug loading, dynamic light scattering, transmission electron microscopy, thermogravimetric analysis, Zeta potential measurement, sterile human cell culture, cell growth quantification, accessing and evaluating transcriptome and clinical data from molecular tumor dataset TCGA, as well as various statistical analyses. RESULTS: We generated homo-dispersed nanofunctionalized DASA as an AuNP@PVA-DASA conjugate. The composite did not enhance the anti-growth effect of DASA on PDAC cell lines. The cell model with high LYN expression showed the strongest response to the therapy. We confirm deregulated Src kinetome activity as a prevalent feature of PDAC by revealing mRNA levels associated with higher malignancy grade of tumors. BLK (B lymphocyte kinase) expression predicts shorter overall survival of diabetic PDAC patients. CONCLUSIONS: Nanofunctionalization of DASA needs further improvement to overcome the therapy resistance of PDAC. LYN mRNA is augmented in tumors with higher malignancy and can serve as a predictive biomarker for the therapy resistance of PDAC cells against DASA. Studying the biological roles of BLK might help to identify underlying molecular mechanisms associated with PDAC in diabetic patients.

A 3'-pre-tRNA-derived small RNA tRF-1-Ser regulated by 25(OH)D promotes proliferation and stemness by inhibiting the function of MBNL1 in breast cancer.

BACKGROUND: We explored the potential novel anticancer mechanisms of 25-hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA-derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. METHODS: Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High-throughput RNA-sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF-1-Ser knockdown. RNA pull-down and high-performance liquid chromatography-mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF-1-Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF-1-Ser on breast cancer. Semi-quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. RESULTS: The expression of tRF-1-Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF-1-Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF-1-Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF-1-Ser plays a vital role in the anticancer effect of 25(OH)D. CONCLUSIONS: In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF-1-Ser in BRCA progression, and suggested that tRF-1-Ser could emerge as a new therapeutic target for BRCA.

Machine learning and new insights for breast cancer diagnosis.

Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and breast thermographic techniques. More recently, machine learning (ML) tools have been increasingly employed in diagnostic medicine for its high efficiency in detection and intervention. The subsequent imaging features and mathematical analyses can then be used to generate ML models, which stratify, differentiate and detect benign and malignant breast lesions. Given its marked advantages, radiomics is a frequently used tool in recent research and clinics. Artificial neural networks and deep learning (DL) are novel forms of ML that evaluate data using computer simulation of the human brain. DL directly processes unstructured information, such as images, sounds and language, and performs precise clinical image stratification, medical record analyses and tumour diagnosis. Herein, this review thoroughly summarizes prior investigations on the application of medical images for the detection and intervention of BC using radiomics, namely DL and ML. The aim was to provide guidance to scientists regarding the use of artificial intelligence and ML in research and the clinic.

Single-cell transcriptomics reveals comprehensive microenvironment and highlights the dysfuntional state of NK cells in endometrioid carcinoma.

Endometrioid endometrial cancer (EEC) is one of the most common gynecologic malignancies. The interaction between cancer cells and the cells in the tumor microenvironment (TME) plays a crucial role in determining disease progression and response to treatment. To better understand the diversity in the TME of ECC, we conducted a comprehensive analysis using single-cell RNA sequencing across 21 samples, including 16 ECC and 5 adjacent normal tissues. We primarily focused on tumor-infiltrating natural killer (NK) cells and their cell-cell interactions with other immune cell types. We identified a CD56dim_DNAJB1 NK cells subset, which had low cytotoxic capability and high stress levels, suggesting a dysfunctional state. This subset showed strong interactions with tumor-associated macrophages through several ligand-receptor pairs. Additionally, we observed that tumor-infiltrating LAMP3+ dendritic cells may inhibit CD8+ T cells or attract regulatory T cells to the tumor area. These dendritic cells also had impaired activation effects on NK cells within the TME. Our study provides valuable insights into the role of NK cells in cancer immunity and highlights the potential of targeting specific NK cell subsets for therapeutic purposes.

Integrating a microRNA signature as a liquid biopsy-based tool for the early diagnosis and prediction of potential therapeutic targets in pancreatic cancer.

INTRODUCTION: Pancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies. MATERIALS AND METHODS: The analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved. RESULTS: Our multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients. CONCLUSION: A panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

Association between Urinary Lead and Female Breast Cancer: A Population-Based Cross-Sectional Study.

BACKGROUND: Previous studies have explored the relationship between serum lead levels and the risk of female breast cancer (FBC). However, it is still uncertain whether urinary lead levels are associated with FBC. This study aimed to investigate the potential association between urinary lead and FBC. METHODS: A cross-sectional case-control study was conducted using the National Health and Nutrition Examination Survey (NHANES), which is a series of cross-sectional, nationally representative surveys of the United States population consisting of 10 survey waves from 1999 to 2018. This study analyzed a total of 2795 female participants (≥20 years), consisting of 210 participants with FBC and 2585 healthy controls. Urinary lead was detected using Inductively Coupled Plasma-Mass Spectrometry, which was divided into four levels by using quartiles-defining cut points. Multivariate logistic regression was used to analyze the association between urinary lead and FBC. RESULTS: Multivariate logistic regression revealed that urinary lead was positively correlated with FBC (Odds ratio [OR], 2.16; 95% confidence interval [CI]: [1.18, 3.95], p < 0.05) in a fully adjusted model. There were significantly increased ORs of FBC in quartile 4 (Q4) and quartile 3 (Q3), compared with the lowest quartile 1 (Q1) (Q4, OR = 1.48, 95% CI [0.89, 2.48]; Q3: OR = 1.01, 95% CI [0.59, 1.73], p for trend = 0.021). No significant interaction effects were observed between urinary lead levels and FBC between the subgroups (age, race, educational status, body mass index (BMI), marital status, family income to poverty ratio, hypertension status, diabetes status, renal function status, smoking history, ever been pregnant, oral contraceptive use, occupation classification, etc.) (All interaction p-value > 0.05). CONCLUSIONS: Urinary lead is likely positively associated with FBC in the US population.

Seven oxidative stress-related genes predict the prognosis of hepatocellular carcinoma.

Predicting the prognosis of hepatocellular carcinoma (HCC) is a major medical challenge and of guiding significance for treatment. This study explored the actual relevance of RNA expression in predicting HCC prognosis. Cox's multiple regression was used to establish a risk score staging classification and to predict the HCC patients' prognosis on the basis of data in the Cancer Genome Atlas (TCGA). We screened seven gene biomarkers related to the prognosis of HCC from the perspective of oxidative stress, including Alpha-Enolase 1(ENO1), N-myc downstream-regulated gene 1 (NDRG1), nucleophosmin (NPM1), metallothionein-3, H2A histone family member X, Thioredoxin reductase 1 (TXNRD1) and interleukin 33 (IL-33). Among them we measured the expression of ENO1, NGDP1, NPM1, TXNRD1 and IL-33 to investigate the reliability of the multi-index prediction. The first four markers' expressions increased successively in the paracellular tissues, the hepatocellular carcinoma samples (from patients with better prognosis) and the hepatocellular carcinoma samples (from patients with poor prognosis), while IL-33 showed the opposite trend. The seven genes increased the sensitivity and specificity of the predictive model, resulting in a significant increase in overall confidence. Compared with the patients with higher-risk scores, the survival rates with lower-risk scores are significantly increased. Risk score is more accurate in predicting the prognosis HCC patients than other clinical factors. In conclusion, we use the Cox regression model to identify seven oxidative stress-related genes, investigate the reliability of the multi-index prediction, and develop a risk staging model for predicting the prognosis of HCC patients and guiding precise treatment strategy.

Efficacy comparisons of solvent-based paclitaxel, liposomal paclitaxel, nanoparticle albumin-bound paclitaxel, and docetaxel after neoadjuvant systemic treatment in breast cancer.

PURPOSE: There are four kinds of taxanes: solvent-based paclitaxel (Sb-P), liposomal paclitaxel (Lps-P), nanoparticle albumin-bound paclitaxel (Nab-P), and docetaxel. This study aims to retrospectively evaluate the efficacy of different taxanes on neoadjuvant systemic treatment (NST) in breast cancer. METHODS: Patients who were diagnosed with breast cancer and had received integral NST from August 2013 to April 2022 were enrolled. The efficacy was divided into total pathological complete response (total-pCR), breast pathological complete response (breast-pCR), and axillary pathological complete response (axillary-pCR) for in-depth analysis and discussion. RESULTS: The choice of taxane was an independent risk factor for total-pCR and breast-pCR rates. The highest total-pCR and breast-pCR rates were found in the Nab-P group. The difference was not significant among all the taxanes in the axillary-pCR rate. CONCLUSION: Nab-P significantly improved the total-pCR and breast-pCR rates. It should be the first choice among taxanes in NST for breast cancer.

Oxidative stress genes define two subtypes of triple-negative breast cancer with prognostic and therapeutic implications.

Introduction: Oxidative stress (OS)-related genes have been confirmed to be closely related to the prognosis of triple-negative breast cancer (TNBC) patients; despite this fact, there is still a lack of TNBC subtype strategies based on this gene guidance. Here, we aimed to explore OS-related subtypes and their prognostic value in TNBC. Methods: Data from The Cancer Genome Atlas (TCGA)-TNBC and Sequence Read Archive (SRA) (SRR8518252) databases were collected, removing batch effects using a combat method before analysis. Consensus clustering analysis identified two OS subtypes (clusters A and B), with cluster A showing a better prognosis. Immune infiltration characteristics were analyzed using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) algorithms, revealing higher ImmuneScore and ESTIMATEscore in cluster A. Tumor-suppressive immune cells, human leukocyte antigen (HLA) genes, and three immune inhibitors were more prevalent in cluster A. Results: An eight-gene signature, derived from differentially expressed genes, was developed and validated as an independent risk factor for TNBC. A nomogram combining the risk score and clinical variables accurately predicted patient outcomes. Finally, we also validated the classification effect of subtypes using hub markers of each subtype in the test dataset. Conclusion: Our study reveals distinct molecular clusters based on OS-related genes to better clarify the reactive oxygen species (ROS)-mediated progression and the crosstalk between the ROS and tumor microenvironment (TME) in this heterogenetic disease, and construct a risk prognostic model which could provide more support for clinical treatment decisions.

Hepatic Krüppel-like factor 14 regulates lipid metabolism in nonalcoholic steatohepatitis mice.

Excessive lipid accumulation is a critical characteristic in the development of nonalcoholic steatohepatitis (NASH). The underlying molecular mechanism, however, is unclear. In this study, we explored whether and how Krüppel-like factor 14 (KLF14) affects hepatic lipid metabolism in NASH. KLF14 expression was detected in NASH patients and mice fed a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD). Adeno-associated viruses and adenoviruses were used to alter hepatic KLF14 expression in vivo or in vitro to investigate how KLF14 functions in lipid regulation. The molecular mechanisms were explored using RNA-seq, luciferase reporter, and ChIP assays. The fatty liver phenotype was analyzed histopathologically, and serum and hepatocyte biochemical parameters were measured. The NASH mouse model developed quickly in C57BL/6J mice fed a CDAHFD for 8 weeks. We found that KLF14 expression was decreased in NASH patients and CDAHFD mice. Oleic acid and palmitic acid treatment also reduced KLF14 levels in hepatocytes. KLF14 knockdown downregulated the genes involved in fatty acid oxidation, promoting the progression of hepatic steatosis. In contrast, hepatic KLF14 overexpression alleviated lipid accumulation and oxidative stress in CDAHFD mice. These effects resulted from direct activation of the PPARα signaling pathway. PPARα inhibition diminished the KLF14 overexpression-reduced protective effects against steatosis in OA&PA-treated MPHs and AAV-KLF14-infected CDAHFD mice. These data reveal that hepatic KLF14 regulates lipid accumulation and oxidative stress through the KLF14-PPARα pathway as NASH progresses. KLF14 may be a novel therapeutic target for hepatic steatosis.

Mendelian Randomization Analyses of Chronic Immune-Mediated Diseases, Circulating Inflammatory Biomarkers, and Cytokines in Relation to Liver Cancer.

Liver cancer is closely linked to chronic inflammation. While observational studies have reported positive associations between extrahepatic immune-mediated diseases and systemic inflammatory biomarkers and liver cancer, the genetic association between these inflammatory traits and liver cancer remains elusive and merits further investigation. We conducted a two-sample Mendelian randomization (MR) analysis, using inflammatory traits as exposures and liver cancer as the outcome. The genetic summary data of both exposures and outcome were retrieved from previous genome-wide association studies (GWAS). Four MR methods, including inverse-variance-weighted (IVW), MR-Egger regression, weighted-median, and weighted-mode methods, were employed to examine the genetic association between inflammatory traits and liver cancer. Nine extrahepatic immune-mediated diseases, seven circulating inflammatory biomarkers, and 187 inflammatory cytokines were analyzed in this study. The IVW method suggested that none of the nine immune-mediated diseases were associated with the risk of liver cancer, with odds ratios of 1.08 (95% CI 0.87-1.35) for asthma, 0.98 (95% CI 0.91-1.06) for rheumatoid arthritis, 1.01 (95% CI 0.96-1.07) for type 1 diabetes, 1.01 (95% CI 0.98-1.03) for psoriasis, 0.98 (95% CI 0.89-1.08) for Crohn's disease, 1.02 (95% CI 0.91-1.13) for ulcerative colitis, 0.91 (95% CI 0.74-1.11) for celiac disease, 0.93 (95% CI 0.84-1.05) for multiple sclerosis, and 1.05 (95% CI 0.97-1.13) for systemic lupus erythematosus. Similarly, no significant association was found between circulating inflammatory biomarkers and cytokines and liver cancer after correcting for multiple testing. The findings were consistent across all four MR methods used in this study. Our findings do not support a genetic association between extrahepatic inflammatory traits and liver cancer. However, larger-scale GWAS summary data and more genetic instruments are needed to confirm these findings.

Mammalian cleavage factor 25 targets KLF14 to inhibit hepatic stellate cell activation and liver fibrosis.

Liver fibrosis is primarily caused by the activation of hepatic stellate cells (HSCs), which results from chronic liver damage. Understanding the pathogenesis of HSC activation could identify new therapeutic targets to treat liver fibrosis. In this study, we examined the protective role of the mammalian cleavage factor I 25 kD subunit (CFIm25, NUDT21) in inhibiting hepatic stellate cell activation. CFIm25 expression was measured in liver cirrhosis patients and a CCl4-induced mouse model. Adeno-associated viruses and adenoviruses were used to alter hepatic CFIm25 expression in vivo and in vitro to investigate how CFIm25 functions in liver fibrosis. The underlying mechanisms were explored using RNA-seq and co-IP assays. Here, we found that CFIm25 expression was drastically decreased in activated murine HSCs and fibrotic liver tissues. CFIm25 overexpression downregulated the expression of genes involved in liver fibrosis, inhibiting the progression of HSC activation, migration and proliferation. These effects resulted from direct activation of the KLF14/PPARγ signaling axis. KLF14 inhibition abrogated the CFIm25 overexpression-mediated reduction in antifibrotic effects. These data reveal that hepatic CFIm25 regulates HSC activation through the KLF14/PPARγ pathway as liver fibrosis progresses. CFIm25 may be a novel therapeutic target for liver fibrosis.

Autotaxin promotes the degradation of the mucus layer by inhibiting autophagy in mouse colitis.

Autotaxin (ATX or ENPP2) is an autocrine enzyme associated with the metabolism of various phospholipids. ATX has recently been identified as a regulatory factor in immune-related and inflammation-associated diseases, such as inflammatory bowel disease, but the exact mechanism is unclear. Here, we treated mice with recombinant ATX protein or an ATX inhibitor to investigate the effect of ATX on colitis in mice and the underlying mechanism. In a mouse model of colitis, ATX expression was increased, autophagy was impaired, and the mucus barrier was disrupted. Recombinant ATX protein promoted intestinal inflammation, inhibited autophagy, and disrupted the mucus barrier, while an ATX inhibitor had the opposite effect. Next, we treated mice that received ATX with an autophagy activator and an adenosine 5'-monophosphate-activated protein kinase (AMPK) agonist. We observed that autophagy activator and AMPK agonist could repair the mucus barrier and alleviate intestinal inflammation in ATX-treated mice. In vitro, we obtained consistent results. Thus, we concluded that ATX could inhibit autophagy through the AMPK pathway, which consequently disordered the mucus barrier and aggravated intestinal inflammation.

Hybrid pedicle screw and modified cortical bone trajectory technique in transforaminal lumbar interbody fusion at L4-L5 segment: finite element analysis.

BACKGROUND: Investigate the biomechanical properties of the hybrid fixation technique with bilateral pedicle screw (BPS) and bilateral modified cortical bone trajectory screw (BMCS) in L4-L5 transforaminal lumbar interbody fusion (TLIF). METHODS:  Three finite element (FE) models of the L1-S1 lumbar spine were established according to the three human cadaveric lumbar specimens. BPS-BMCS (BPS at L4 and BMCS at L5), BMCS-BPS (BMCS at L4 and BPS at L5), BPS-BPS (BPS at L4 and L5), and BMCS-BMCS (BMCS at L4 and L5) were implanted into the L4-L5 segment of each FE model. The range of motion (ROM) of the L4-L5 segment, von Mises stress of the fixation, intervertebral cage, and rod were compared under a 400-N compressive load with 7.5 Nm moments in flexion, extension, bending, and rotation. RESULTS:  BPS-BMCS technique has the lowest ROM in extension and rotation, and BMCS-BMCS technique has the lowest ROM in flexion and lateral bending. The BMCS-BMCS technique showed maximal cage stress in flexion and lateral bending, and the BPS-BPS technique in extension and rotation. Compared to the BPS-BPS and BMCS-BMCS technique, BPS-BMCS technique presented a lower risk of screw breakage and BMCS-BPS technique presented a lower risk of rod breakage. CONCLUSION:  The results of this study support that the use of the BPS-BMCS and BMCS-BPS techniques in TLIF surgery for offering the superior stability and a lower risk of cage subsidence and instrument-related complication.

Nanoparticle albumin-bound paclitaxel-based neoadjuvant regimen: A promising treatment option for HER2-low-positive breast cancer.

This study aimed to compare the efficacy of neoadjuvant systemic therapy (NST) with solvent-based paclitaxel (Sb-P), liposomal paclitaxel (Lps-P), nanoparticle albumin-bound paclitaxel (Nab-P), and docetaxel in human epidermal growth factor receptor 2 (HER2)-low-positive and HER2-zero breast cancers. A total of 430 patients receiving 2-weekly dose-dense epirubicin and cyclophosphamide (EC) followed by 2-weekly paclitaxel (Sb-P, Lps-P, or Nab-P), or 3-weekly EC followed by 3-weekly docetaxel for NST were enrolled in the study. In HER2-low-positive patients, the pathological complete response (pCR) rate in Nab-P group was significantly higher than that in the other three paclitaxel groups (2.8 % in Sb-P group, 4.7 % in Lps-P group, 23.2 % in Nab-P group and 3.2 % in docetaxel group, p < 0.001). In HER2-zero patients, the pCR rate did not differ significantly among the four paclitaxel groups (p = 0.278). The NST regimen containing Nab-P could be considered a promising treatment option in HER2-low-positive breast cancer.

An unusual case of immune-related gastritis in one patient receiving toripalimab therapy.

PD-1 inhibitors contribute to immune response against malignancies. These drugs also result in serial side effects. Here the authors report a case of immune-related gastritis induced by PD-1 inhibitor. A female with metastatic lung cancer developed severe epigastric pain and acid reflux during treatment with toripalimab. She underwent several gastroscopies, which showed progressively worse gastritis. After discontinuing toripalimab, those symptoms were resolved. This rare report highlights gastritis associated with toripalimab, describes the symptoms and histology features and records the progression of this side effect and the corresponding treatment. Based on the improvement after toripalimab withdrawal, the authors believed that she had autoimmune gastritis caused by toripalimab. This case reminds us that correct diagnosis and proper management are critical to patients undergoing treatment with PD-1 inhibitors.

Toripalimab is a kind of PD-1 inhibitor, which is a new drug for cancer treatment. Briefly, this drug fights cancer effectively by strengthening the body's immune system. However, these drugs also result in serial side effects. Here the authors report a case of severe gastritis induced by a PD-1 inhibitor. An Asian female patient with lung cancer gradually developed bad stomachache, acidity and heartburn during treatment with toripalimab. After several hospitalizations, she was diagnosed with toripalimab-induced gastritis, which is associated with a disruption of the immune system. Discontinuation of this medication put her in remission. Notably, there is no mention of the possibility of gastritis induced by toripalimab in the drug description and related documents. By learning from this case, the authors will be better equipped to identify and manage toripalimab-induced gastritis in the future, which will lessen suffering and increase the survival rates of patients.

Volume change rate before and after neoadjuvant systemic therapy of breast cancer is an efficacious evaluation index to predict pathological complete response.

Neoadjuvant systemic therapy (NST) is widely applied in breast cancer treatment, but individuals respond differently to the same NST regimen. It is unclear which patients should adjust their NST regimen and what such an adjustment should be, especially for patients with radiologically partial response (PR). This study aimed to identify a quantitative efficacy evaluation index to evaluate the therapeutic effect of NST. 164 patients were enrolled in this study received four cycles of epirubicin and cyclophosphamide (EC), followed by four cycles of taxanes with trastuzumab [T(H)], if needed. Of patients with a volume change rate of EC treatment (δV1) below 0.80, more than half benefited from subsequent T(H) treatment compared with EC treatment. Importantly, for δV1 of 0.80 and higher, patients' subsequent T(H) treatment was not as efficient as previous EC treatment and they have a lower pathological complete response (pCR) rate. Across all patients, nanoparticle albumin-bound paclitaxel had a numerically higher pCR rate over other taxanes in patients with triple-negative breast cancer. This study showed that the volume change rate is better than the diameter change rate in monitoring the therapeutic effect of NST. Furthermore, δV1 is a good quantitative efficacy evaluation index to distinguish patients resistant to EC treatment and predict the pCR rate and guide the adjustment of individualized NST regimens.

Chromatin Regulator-Related Gene Signature for Predicting Prognosis and Immunotherapy Efficacy in Breast Cancer.

Background: Many studies have found that chromatin regulators (CRs) are correlated with tumorigenesis and disease prognosis. Here, we attempted to build a new CR-related gene model to predict breast cancer (BC) survival status. Methods: First, the CR-related differentially expressed genes (DEGs) were screened in normal and tumor breast tissues, and the potential mechanism of CR-related DEGs was determined by function analysis. Based on the prognostic DEGs, the Cox regression model was applied to build a signature for BC. Then, survival and receiver operating characteristic (ROC) curves were performed to validate the signature's efficacy and identify its independent prognostic value. The CIBERSORT and tumor immune dysfunction and exclusion (TIDE) algorithms were used to assess the immune cells infiltration and immunotherapy efficacy for this signature, respectively. Additionally, a novel nomogram was also built for clinical decisions. Results: We identified 98 CR-related DEGs in breast tissues and constructed a novel 6 CR-related gene signature (ARID5A, ASCL1, IKZF3, KDM4B, PRDM11, and TFF1) to predict the outcome of BC patients. The prognostic value of this CR-related gene signature was validated with outstanding predictive performance. The TIDE analysis revealed that the high-risk group patients had a better response to immune checkpoint blockade (ICB) therapy. Conclusion: A new CR-related gene signature was built, and this signature could provide the independent predictive capability of prognosis and immunotherapy efficacy for BC patients.

Prognostic analysis of three forms of Ki-67 in patients with breast cancer with non-pathological complete response before and after neoadjuvant systemic treatment.

BACKGROUND: Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non-pCR patients. To date, the prognostic role in terms of disease-free survival (DFS) between the terminal index of Ki-67 after surgery (Ki-67T ) and the combination of the baseline Ki-67 at biopsy before NST (Ki-67B ) and the percentage change in Ki-67 before and after NST (Ki-67C ) has not been compared. AIM: This study aimed to explore the most useful form or combination of Ki-67 that can provide prognostic information to non-pCR patients. PATIENTS AND METHODS: We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane. RESULTS: Among all the patients, 335 did not achieve pCR (with a follow-up period of ≥1 year). The median follow-up duration was 36 months. The optimal cutoff value of Ki-67C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki-67C (p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki-67C and Ki-67T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki-67B and Ki-67C showed a significantly higher area under the curve at years 3 and 5 than Ki-67T (p = 0.029 and p = 0.022, respectively). CONCLUSIONS: Ki-67C and Ki-67T were good independent predictors of DFS, whereas Ki-67B was a slightly inferior predictor. The combination of Ki-67B and Ki-67C is superior to Ki-67T for predicting DFS, especially at longer follow-ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high-risk patients.