Neoplasia最新文献

Alterations in cellular metabolism are important hallmarks of glioblastoma(GBM). Metabolic reprogramming is a critical feature as it meets the higher nutritional demand of tumor cells, including proliferation, growth, and survival. Many genes, proteins, and metabolites associated with GBM metabolism reprogramming have been found to be aberrantly expressed, which may provide potential targets for cancer treatment. Therefore, it is becoming increasingly important to explore the role of internal and external factors in metabolic regulation in order to identify more precise therapeutic targets and diagnostic markers for GBM. In this review, we define the metabolic characteristics of GBM, investigate metabolic specificities such as targetable vulnerabilities and therapeutic resistance, as well as present current efforts to target GBM metabolism to improve the standard of care.

Introduction

Colorectal cancer is the third most common cause of cancer death. Rectal cancer makes up a third of all colorectal cases. Treatment for locally advanced rectal cancer includes chemoradiation followed by surgery. We have previously identified ST6GAL1 as a cause of resistance to chemoradiation in vitro and hypothesized that it would be correlated with poor response in human derived models and human tissues.

Methods

Five organoid models were created from primary human rectal cancers and ST6GAL1 was knocked down via lentivirus transduction in one model. ST6GAL1 and Cleaved Caspase-3 (CC3) were assessed after chemoradiation via immunostaining. A tissue microarray (TMA) was created from twenty-six patients who underwent chemoradiation and had pre- and post-treatment specimens of rectal adenocarcinoma available at our institution. Immunohistochemistry was performed for ST6GAL1 and percent positive cancer cell staining was assessed and correlation with pathological grade of response was measured.

Results

Organoid models were treated with chemoradiation and both ST6GAL1 mRNA and protein significantly increased after treatment. The organoid model targeted with ST6GAL1 knockdown was found to have increased CC3 after treatment. In the tissue microarray, 42 percent of patient samples had an increase in percent tumor cell staining for ST6GAL1 after treatment. Post-treatment percent staining was associated with a worse grade of treatment response (p = 0.01) and increased staining post-treatment compared to pre-treatment was also associated with a worse response (p = 0.01).

Conclusion

ST6GAL1 is associated with resistance to treatment in human rectal cancer and knockdown in an organoid model abrogated resistance to apoptosis caused by chemoradiation.

Purpose

Helicobacter pylori (H. pylori) is a significant risk factor for development of gastric cancer (GC), one of the deadliest malignancies in the world. However, the mechanism by which H. pylori induces gastric oncogenesis remains unclear. Here, we investigated the function of IL-6 in gastric oncogenesis and macrophage-epithelial cell interactions.

Methods

We analyzed publicly available datasets to investigate the expression of IL-6 and infiltration of M2 macrophages in GC tissues, and determine the inter-cellular communication in the context of IL-6. Human gastric epithelial and macrophage cell lines (GES-1 and THP-1-derived macrophages, respectively) were used in mono- and co-culture experiments to investigate autocrine-and paracrine induction of IL-6 expression in response to H. pylori or IL-6 stimulation.

Results

We found that IL-6 is highly expressed in GC and modulates survival. M2 macrophage infiltration is predominant in GC and drives an IL-6 mediated communication with gastric epithelium cells. In vitro, IL-6 triggers its own expression in GES-1 and THP-1-derived macrophages cells. In addition, these cell lines are able to upregulate each other's IL-6 levels in an autocrine fashion, which is enhanced by H. pylori stimulation.

Conclusion

This study indicates that IL-6 in the tumor microenvironment is essential for intercellular communication. We show that H. pylori enhances an IL-6-driven autocrine and paracrine positive feedback loop between macrophages and gastric epithelial cells, which may contribute to gastric carcinogenesis.

Glioblastoma is the deadliest form of brain tumor. The presence of the blood–brain barrier (BBB) significantly hinders chemotherapy, necessitating the development of innovative treatment options for this tumor. This report presents the in vitro and in vivo efficacy of an antibody–drug conjugate (ADC) that targets glypican-1 (GPC1) in glioblastoma. The GPC1-ADC was created by conjugating a humanized anti-GPC1 antibody (clone T2) with monomethyl auristatin E (MMAE) via maleimidocaproyl-valine-citrulline-p-aminobenzyloxycarbonyl linkers. Immunohistochemical staining analysis of a glioblastoma tissue microarray revealed that GPC1 expression was elevated in more than half of the cases. GPC1-ADC, when bound to GPC1, was efficiently and rapidly internalized in glioblastoma cell lines. It inhibited the growth of GPC1-positive glioma cell lines by inducing cell cycle arrest in the G2/M phase and triggering apoptosis in vitro. We established a heterotopic xenograft model by subcutaneously implanting KALS-1 and administered GPC1-ADC intravenously. GPC1-ADC significantly inhibited tumor growth and increased the number of mitotic cells. We also established an orthotopic xenograft model by intracranially implanting luciferase-transfected KS-1-Luc#19. After injecting Evans blue and resecting brain tissues, dye leakage was observed in the implantation area, confirming BBB disruption. We administered GPC1-ADC intravenously and measured the luciferase activity using an in vivo imaging system. GPC1-ADC significantly inhibited tumor growth and extended survival. In conclusion, GPC1-ADC demonstrated potent intracranial activity against GPC1-positive glioblastoma in an orthotopic xenograft model. These results indicate that GPC1-ADC could represent a groundbreaking new therapy for treating glioblastoma beyond the BBB.

While BRAF alterations have been established as a driver in various solid malignancies, the characterization of BRAF alterations in prostate cancer (PCa) has not been thoroughly interrogated. By bioinformatics analysis, we first found that BRAF alterations were associated with advanced PCa and exhibited mutually exclusive pattern with ERG alteration across multiple cohorts. Of the most interest, recurrent non-V600 BRAF mutations were found in 3 of 21 (14.3 %) PCa patients demonstrating IDC-P morphology. Furthermore, experimental overexpression of BRAF^K601E and BRAF^L597R exhibited emergence of oncogenic phenotypes with intensified MAPK signaling in vitro, which could be targeted by MEK inhibitors. Comparison of the incidence of BRAF alterations in IDC-P between western and Chinese ancestry revealed an increased prevalence in the Chinese population. The BRAF mutation may represent important genetic alteration in a subset of IDC-P, highlighting the role of MAPK signaling pathway in this subtype of PCa. To the best of knowledge, this is the first description of non-V600 BRAF mutation in setting of IDC-P, which may in part explain the aggressive phenotype seen in IDC-P and could also bring more treatment options for PCa patients with IDC-P harboring such mutations.

Background

Breast cancer in different molecular subtypes, which is determined by the overexpression rates of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR), and Ki67, exhibit distinct symptom characteristics and sensitivity to different treatment. The immunohistochemical method, one of the most common detecting tools for tumour markers, is heavily relied on artificial judgment and in clinical practice, with an inherent limitation in interpreting stability and operating efficiency. Here, a holistic intelligent breast tumour diagnosis system has been developed for tumour-markeromic analysis, combining the automatic interpretation and clinical suggestion.

Methods

The holistic intelligent breast tumour diagnosis system included two main modules. The interpreting modules were constructed based on convolutional neural network, for comprehensively extracting and analyzing the multi-features of immunostaining. Referring to the clinical classification criteria, the interpreting results were encoded in a low-dimensional feature representation in the subtyping module, to efficiently output a holistic detecting result of the critical tumour-markeromic with diagnosis suggestions on molecular subtypes.

Results

The overexpression rates of HER2, ER, PR, and Ki67, as well as an effective determination of molecular subtypes were successfully obtained by this diagnosis system, with an average sensitivity of 97.6 % and an average specificity of 96.1 %, among those, the sensitivity and specificity for interpreting HER2 were up to 99.8 % and 96.9 %.

Conclusion

The holistic intelligent breast tumour diagnosis system shows improved performance in the interpretation of immunohistochemical images over pathologist-level, which can be expected to overcome the limitations of conventional manual interpretation in efficiency, precision, and repeatability.

Background

Despite promising overall survival of stage I lung adenocarcinoma (LUAD) patients, 10-25 % of them still went through recurrence after surgery. [1] While it is still disputable whether adjuvant chemotherapy is necessary for stage I patients. [2] IASLC grading system for non-mucinous LUAD shows that minor high-grade patterns are significant indicator of poor prognosis. [3] Other risk factors, such as, pleura invasion, lympho-vascular invasion, STAS, etc. are also related to poor prognosis. [4-6] There still lack evidence whether IASLC grade itself or together with other risk factors can guide the use of adjuvant therapy in stage I patients. In this article, we tried to establish a multi-variable recurrence prediction model for stage I LUAD patients that is able to identify candidates of adjuvant chemotherapy.

Methods

We retrospectively collected patients who underwent lung surgery from 2018.8.1 to 2018.12.31 at our institution and diagnosed with lung adenocarcinoma pT1-2aN0M0 (stage I). Clinical data, manifestation on CT scan, pathologic features, driver gene mutations and follow-up information were collected. Cox proportional hazards regression analyses were performed utilizing the non-adjuvant cohort to predict disease free survival (DFS) and a nomogram was constructed and applied to the total cohort. Kaplan-Meier method was used to compare DFS between groups. Statistical analysis was conducted by R version 3.6.3.

Findings

A total of 913 stage I LUAD patients were included in this study. Median follow-up time is 48.1 months.4-year and 5-year DFS are 92.9 % and 89.6 % for the total cohort. 65 patient experienced recurrence or death. 4-year DFS are 97.0 %,94.6 % and 76.2 %, and 5-year DFS are 95.5 %, 90.0 % and 74.1 % in IASLC Grade1, 2 and 3, respectively(p < 0.0001). High-risk patients defined by single risk factors, such as, IASLC grade 3, pleura invasion, STAS, less LN resected could not benefit from adjuvant therapy. A LASSO-COX regression model was built and patients are divided into high-risk and low-risk groups. In the high-risk group, patients underwent adjuvant chemotherapy have longer DFS than those who did not (p = 0.024), while in the low-risk group, patients underwent adjuvant chemotherapy have inferior DFS than those who did not (p < 0.001).

Interpretation

IASLC grading is a significant indicator of DFS, however it could not guide adjuvant therapy in our stage I LUAD cohort. Growth patterns and T indicators together with other risk factors could identify high-risk patients that are potential candidate of adjuvant therapy, including some stage IA LUAD patients.

Nasopharyngeal carcinoma (NPC) and oropharyngeal carcinoma (OPC) are subtypes of head and neck cancer with different treatment effects due to the heterogeneity of tumor microenvironments. This study was to investigate the distinctive tumor microenvironments of NPC and OPC. Analyzing single-cell data from 10 cases of each subtype, we reveal significant differences in cellular composition, with NPC microenvironment dominated by T/NK and B cells, and OPC characterized by prevalent epithelial cells and fibroblasts. Dynamic transitions of CD8 T cells are observed in both tumor types, involving shifts from naivety to cytotoxicity, proliferation, and eventual exhaustion/exhausted states. Additionally, Tregs exhibit heightened proliferative abilities in later developmental stages, concomitant with exhaustion. These highly proliferative T cells and Tregs manifest elevated glycolysis and lactate metabolism activities. Furthermore, we explore intercellular communication between glycolytic malignant epithelial cells and these proliferative T cells. These findings offer comprehensive insights into the heterogeneity of tumor microenvironments and provide a solid foundation for future therapeutic strategies and targeted interventions.

Multiple myeloma is a hematological malignancy that has evolved from antibody-secreting B lymphocytes. Like other types of cancers, myeloma cells have acquired functional capabilities which are referred to as “Hallmarks of Cancer”, and one of their most important features is the metabolic disorders. Due to the high secretory load of the MM cells, the first-line medicine proteasome inhibitors have found their pronounced effects in MM cells for blocking the degradation of misfolded proteins, leading to their accumulation in the ER and overwhelming ER stress. Moreover, proteasome inhibitors have been reported to be effective in myeloma by targeting glucose, lipid, amino acid metabolism of MM cells. In this review, we have described the abnormal metabolism of the three major nutrients, such as glucose, lipid and amino acids, which participate in the cellular functions. We have described their roles in myeloma progression, how they could be exploited for therapeutic purposes, and current therapeutic strategies targeting these metabolites, hoping to uncover potential novel therapeutic targets and promote the development of future therapeutic approaches.