Diverse Tumor Research Articles

Siglec15/TGF‐β bispecific antibody mediates synergistic anti‐tumor response against 4T1 triple negative breast cancer in mice

AbstractAn ideal tumor‐specific immunomodulatory therapy should both preferentially target the tumor, while simultaneously reduce the immunosuppressive environment within the tumor. This guiding principle led us to explore engineering Siglec‐15 (S15) targeted bispecific antibody (bsAb) to enhance therapy against triple negative breast cancer (TNBC). S15 appears to be exclusively expressed on macrophages and diverse tumor cells, including human and mouse 4T1 TNBC. TGF‐β is a growth hormone frequently associated with increased tumor invasiveness, including in TNBC. Here, to overcome the immune‐suppressive environment within TNBC tumors to enable more effective cancer therapy, we engineered a bispecific antibody (bsAb) targeting both Siglec15 and TGF‐β. In mice engrafted with orthotopic 4T1 tumors, S15/TGF‐β bsAb treatment was highly effective in suppressing tumor growth, not only compared to control monoclonal antibody (mAb) but also markedly more effective than mAbs against S15 alone, against TGF‐β alone, as well as a cocktail of both anti‐S15 and anti‐TGF‐β mAbs. We did not detect liver and lung metastasis in mice treated with S15/TGF‐β bsAb, unlike all other treatment groups at the end of the study. The enhanced anti‐tumor response observed with S15/TGF‐β bsAb correlated with a less immunosuppressive environment in the tumor. These results underscore S15‐targeted bsAb as a promising therapeutic strategy for TNBC, and possibly other S15 positive solid tumors.

FLI1 induces erythroleukemia through opposing effects on UBASH3A and UBASH3B expression

BackgroundFLI1 is an oncogenic transcription factor that promotes diverse malignancies through mechanisms that are not fully understood. Herein, FLI1 is shown to regulate the expression of Ubiquitin Associated and SH3 Domain Containing A/B (UBASH3A/B) genes. UBASH3B and UBASH3A are found to act as an oncogene and tumor suppressor, respectively, and their combined effect determines erythroleukemia progression downstream of FLI1.MethodsPromoter analysis combined with luciferase assays and chromatin immunoprecipitation (ChIP) analysis were applied on the UBASH3A/B promoters. RNAseq analysis combined with bioinformatic was used to determine the effect of knocking-down UBASH3A and UBASH3B in leukemic cells. Downstream targets of UBASH3A/B were inhibited in leukemic cells either via lentivirus-shRNAs or small molecule inhibitors. Western blotting and RT-qPCR were used to determine transcription levels, MTT assays to assess proliferation rate, and flow cytometry to examine apoptotic index.ResultsKnockdown of FLI1 in erythroleukemic cells identified the UBASH3A/B genes as potential downstream targets. Herein, we show that FLI1 directly binds to the UBASH3B promoter, leading to its activation and leukemic cell proliferation. In contrast, FLI1 indirectly inhibits UBASH3A transcription via GATA2, thereby antagonizing leukemic growth. These results suggest oncogenic and tumor suppressor roles for UBASH3B and UBASH3A in erythroleukemia, respectively. Mechanistically, we show that UBASH3B indirectly inhibits AP1 (FOS and JUN) expression, and that its loss leads to inhibition of apoptosis and acceleration of proliferation. UBASH3B also positively regulates the SYK gene expression and its inhibition suppresses leukemia progression. High expression of UBASH3B in diverse tumors was associated with worse prognosis. In contrast, UBASH3A knockdown in erythroleukemic cells increased proliferation; and this was associated with a dramatic induction of the HSP70 gene, HSPA1B. Accordingly, knockdown of HSPA1B in erythroleukemia cells significantly accelerated leukemic cell proliferation. Accordingly, overexpression of UBASH3A in different cancers was predominantly associated with good prognosis. These results suggest for the first time that UBASH3A plays a tumor suppressor role in part through activation of HSPA1B.ConclusionsFLI1 promotes erythroleukemia progression in part by modulating expression of the oncogenic UBASH3B and tumor suppressor UBASH3A.

Pan-cancer analysis reveals PDK family as potential indicators related to prognosis and immune infiltration

Pyruvate dehydrogenase kinases (PDKs) play a key role in glucose metabolism by exerting negative regulation over pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibition of PDKs holds the potential to enhance PDC activity, prompting cells to adopt a more aerobic metabolic profile. Consequently, PDKs emerge as promising targets for condition rooted in metabolic dysregulation, including malignance and diabetes. However, a comprehensive exploration of the distinct contribution of various PDK family members, particularly PDK3, across diverse tumor types remain incomplete. This study undertakes a systematic investigation of PDK family expression patterns, forging association with clinical parameters, using data from the TCGA and GTEx datasets. Survival analysis of PDKs is executed through both Kaplan–Meier analysis and COX regression analysis. Furthermore, the extent of immune infiltration is assessed by leveraging the CIBERSORT algorithm. Our study uncovers pronounced genetic heterogeneity among PDK family members, coupled with discernible clinical characteristic. Significantly, the study establishes the potential utility of PDK family genes as prognostic indicators and as predictors of therapeutic response. Additionally, our study sheds light on the immune infiltration profile of PDK family. The results showed the intimate involvement of these genes in immune-related metrics, including immune scoring, immune subtypes, tumor-infiltrating lymphocytes, and immune checkpoints expression. In sum, the findings of this study offer insightful strategies to guide the therapeutic direction, aiming at leveraging the impact of PDK family genes in cancer treatment.

A preliminary study of IgG4 expression and its prognostic significance in oral squamous cell carcinoma

BackgroundIgG4, which plays a pivotal role in the progression of phenotypically diverse tumors, serves as a prognostic marker because of its influence on cancer immunity. Nevertheless, the functions of IgG4 in tongue squamous cell carcinoma (TSCC) remained to be identified.MethodsTo evaluate the significance of IgG4 expression in TSCC, we performed immunohistochemical analysis of patients with TSCC (n = 50) to evaluate the correlation of IgG4 expression with patients’ clinicopathological features and prognoses.ResultsHigher IgG4 expression detected in TSCC tissues was associated with the less advanced mode of invasion (Yamamoto-Kohama [YK] 1–3) (P = 0.031) and with well-differentiated TSCC (P = 0.077). Kaplan–Meier analyses revealed that the higher IgG4 expression group exhibited better prognosis indicated by overall survival (OS) (P = 0.04) and recurrence-free survival (RFS) (P = 0.016). Univariate analysis of OS indicated that IgG4 expression was associated with longer OS (P = 0.061), and multivariate analysis of RFS revealed that IgG4 expression served as an independent prognostic factor for longer RFS (P = 0.005).ConclusionThese results indicate that relatively higher IgG4 levels serve as a favorable prognostic factor for TSCC.

Phospholipase A2 enzymes PLA2G2A and PLA2G12B as potential diagnostic and prognostic biomarkers in cholangiocarcinoma.

Phospholipase A2 (PLA2) enzymes are pivotal in various biological processes, such as lipid mediator production, membrane remodeling, bioenergetics, and maintaining the body surface barrier. Notably, these enzymes play a significant role in the development of diverse tumors. To systematically and comprehensively explore the expression of the PLA2 family genes and their potential implications in cholangiocarcinoma (CCA). We conducted an analysis of five CCA datasets from The Cancer Genome Atlas and the Gene Expression Omnibus. The study identified differentially expressed genes between tumor tissues and adjacent normal tissues, with a focus on PLA2G2A and PLA2G12B. Gene Set Enrichment Analysis was utilized to pinpoint associated pathways. Moreover, relevant hub genes and microRNAs for PLA2G2A and PLA2G12B were predicted, and their correlation with the prognosis of CCA was evaluated. PLA2G2A and PLA2G12B were discerned as differentially expressed in CCA, manifesting significant variations in expression levels in urine and serum between CCA patients and healthy individuals. Elevated expression of PLA2G2A was correlated with poorer overall survival in CCA patients. Additionally, the study delineated pathways and miRNAs associated with these genes. Our findings suggest that PLA2G2A and PLA2G12B may serve as novel potential diagnostic and prognostic markers for CCA. The increased levels of these genes in biological fluids could be employed as non-invasive markers for CCA, and their expression levels are indicative of prognosis, underscoring their potential utility in clinical settings.

LAPTM4B-mediated hepatocellular carcinoma stem cell proliferation and MDSC migration: implications for HCC progression and sensitivity to PD-L1 monoclonal antibody therapy

In hepatocellular carcinoma (HCC), immunotherapy is vital for advanced-stage patients. However, diverse individual responses and tumor heterogeneity have resulted in heterogenous treatment outcomes. Our mechanistic investigations identified LAPTM4B as a crucial gene regulated by ETV1 (a transcription factor), especially in liver cancer stem cells (LCSCs). The influence of LAPTM4B on LCSCs is mediated via the Wnt1/c-Myc/β-catenin pathway. CXCL8 secretion by LAPTM4B drove myeloid-derived suppressor cell (MDSC) migration, inducing unfavorable patient prognosis. LAPTM4B affected PD-L1 receptor expression in tumor microenvironment and enhanced tumor suppression induced by PD-L1 monoclonal antibodies in HCC patients. LAPTM4B up-regulation is correlated with adverse outcomes in HCC patients, sensitizing them to PD-L1 monoclonal antibody therapy.

Proteomics analysis of histone deacetylase inhibitor-resistant solid tumors reveals resistant signatures and potential drug combinations.

Histone deacetylase inhibitors (HDACis) are important drugs for cancer therapy, but the indistinct resistant mechanisms of solid tumor therapy greatly limit their clinical application. In this study we conducted HDACi-perturbated proteomics and phosphoproteomics analyses in HDACi-sensitive and -resistant cell lines using a tandem mass tag (TMT)-based quantitative proteomic strategy. We found that the ribosome biogenesis proteins MRTO4, PES1, WDR74 and NOP16 vital to tumorigenesis might regulate the tumor sensitivity to HDACi. By integrating HDACi-perturbated protein signature with previously reported proteomics and drug sensitivity data, we predicted and validated a series of drug combination pairs potentially to enhance the sensitivity of HDACi in diverse solid tumor. Functional phosphoproteomic analysis further identified the kinase PDK1 and ROCK as potential HDACi-resistant signatures. Overall, this study reveals the potential HDACi-resistant signatures and may provide promising drug combination strategies to attenuate the resistance of solid tumor to HDACi.

PFKFB3 facilitates cell proliferation and migration in anaplastic thyroid carcinoma via the WNT/β-catenin signaling pathway.

Despite the involvement of 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase3 (PFKFB3) in the proliferation and metastasis of diverse tumor types, its biological functions and related molecular mechanisms in anaplastic thyroid carcinoma (ATC) remain largely unclear. Datasets from the Gene Expression Omnibus, the Cancer Genome Atlas and immunohistochemistry (IHC) analyses were employed to measure the expression level of PFKFB3 in ATC. A series of assays were performed to analyze the role of PFKFB3 and its inhibitor KAN0438757 in ATC cell proliferation and migration. Furthermore, Western blotting (WB), IHC and luciferase reporter assay were conducted to investigate the potential mechanisms underlying the involvement of PFKFB3 and KAN0438757 in ATC. Additionally, we established a subcutaneous xenograft tumor model in nude mice to evaluate the in vivo tumor growth. PFKFB3 exhibited a significant increase in its expression level in ATC tissues. The overexpression of PFKFB3 resulted in the stimulation of ATC cell proliferation and migration. Furthermore, this overexpression was associated with the elevated expression levels of p-AKT (ser473), p-GSK3α/β (ser21/9), nuclear β-catenin, fibronectin1 (FN1), matrix metallopeptidase 9 (MMP-9) and cyclin D1. It also promoted the nuclear translocation of β-catenin and the transcription of downstream molecules. Conversely, contrasting results were observed with the downregulation or KAN0438757-mediated inhibition of PFKFB3 in ATC cells. The selective AKT inhibitor MK2206 was noted to reverse the increased expression of p-AKT (ser473) and p-GSK3α/β (ser21/9) induced by PFKFB3 overexpression. The level of lactate was increased in PFKFB3-overexpressing ATC cells, while the presence of KAN0438757 inhibited lactate production. Moreover, the simultaneous use of PFKFB3 downregulation and KAN0438757 was found to suppress subcutaneous tumor growth in vivo. PFKFB3 can enhance ATC cell proliferation and migration via the WNT/β-catenin signaling pathway and plays a crucial role in the regulation of aerobic glycolysis in ATC cells.

Impact of metronomic trabectedin combined with low-dose cyclophosphamide on sarcoma microenvironment and correlation with clinical outcome: results from the TARMIC study.

Soft tissue sarcomas (STS) are diverse mesenchymal tumors with few therapeutic options in advanced stages. Trabectedin has global approval for treating STS patients resistant to anthracycline-based regimens. Recent pre-clinical data suggest that trabectedin's antitumor activity extends beyond tumor cells to influencing the tumor microenvironment (TME), especially affecting tumor-associated macrophages and their pro-tumoral functions. We present the phase I/II results evaluating a combination of metronomic trabectedin and low-dose cyclophosphamide on the TME in patients with advanced sarcomas. 50 patients participated: 20 in phase I and 30 in phase II. Changes in the TME were assessed in 28 patients using sequential tumor samples at baseline and day two of the cycle. Treatment notably decreased CD68 + CD163 + macrophages in biopsies from tumor lesions compared to pre-treatment samples in 9 of the 28 patients after 4 weeks. Baseline CD8 + T cell presence increased in 11 of these patients. In summary, up to 57% of patients exhibited a positive immunological response marked by reduced M2 macrophages or increased CD8 + T cells post-treatment. This positive shift in the TME correlated with improved clinical benefit and progression-free survival. This study offers the first prospective evidence of trabectedin's immunological effect in advanced STS patients, highlighting a relationship between TME modulation and patient outcomes.This study was registered with ClinicalTrial.gov, number NCT02406781.

Evaluation of immunohistochemical expression of novel neuroendocrine marker INSM1 and histological tumor growth pattern in well-differentiated neuroendocrine tumors of the appendix: 15-year single tertiary center experience.

Well-differentiated neuroendocrine tumors of the appendix (A-WDNET) are the most common neoplasms of the appendix but are rare and incidental. INSM1 is a novel transcription factor marker with high sensitivity and specificity for neuroendocrine differentiation. It may display architecturally diverse tumor growth patterns including solid, nest, insular trabecular, and acinar. The aim of this study was to determine the staining expression of INSM1 in A-WDNETs and detail the morphological tumor growth patterns. INSM1 immunohistochemistry was performed on 35 A-WDNET patients. Tumors were histologically classified according to their growth patterns. Thirty-five patients, 60% of whom were male, had a mean age of 30 years at diagnosis and a mean tumor size of 0.9 cm. Eight percent of the tumors invaded the mucosa/submucosa, 34.3% showed invasion into the muscularis propria, 57.1% showed invasion into the subserosa or mesoappendix, LN metastasis was observed in two patients, lymph-vascular invasion in two patients, and perineural invasion in five patients. Ninety-four percent of the tumors were grade 1, the mitotic rate was >2% in two cases, and Ki-67 PI was >3% in two cases. INSM1 was positive in all cases (100%), 1+ 8.6%, 2+ 5.7%, 3+ 17.1%, 4+ 68.6%, weak staining in 11.4%, moderate staining in 22.9%, and strong staining in 67.7%. Type A histological growth pattern was observed in 54.3%, type B in 31.4%, and type C in 14.3% architecturally. INSM1 was positive in all A-WDNET morphological patterns and was 100% sensitive. INSM1 IHC can be used as an alternative to traditional neuroendocrine markers or in combination with the diagnosis of neuroendocrine tumors.

An N-Shaped Lightweight Network with a Feature Pyramid and Hybrid Attention for Brain Tumor Segmentation.

Brain tumor segmentation using neural networks presents challenges in accurately capturing diverse tumor shapes and sizes while maintaining real-time performance. Additionally, addressing class imbalance is crucial for achieving accurate clinical results. To tackle these issues, this study proposes a novel N-shaped lightweight network that combines multiple feature pyramid paths and U-Net architectures. Furthermore, we ingeniously integrate hybrid attention mechanisms into various locations of depth-wise separable convolution module to improve efficiency, with channel attention found to be the most effective for skip connections in the proposed network. Moreover, we introduce a combination loss function that incorporates a newly designed weighted cross-entropy loss and dice loss to effectively tackle the issue of class imbalance. Extensive experiments are conducted on four publicly available datasets, i.e., UCSF-PDGM, BraTS 2021, BraTS 2019, and MSD Task 01 to evaluate the performance of different methods. The results demonstrate that the proposed network achieves superior segmentation accuracy compared to state-of-the-art methods. The proposed network not only improves the overall segmentation performance but also provides a favorable computational efficiency, making it a promising approach for clinical applications.

An inflamed tumor cell subpopulation promotes chemotherapy resistance in triple negative breast cancer

Individual cancers are composed of heterogeneous tumor cells with distinct phenotypes and genotypes, with triple negative breast cancers (TNBC) demonstrating the most heterogeneity among breast cancer types. Variability in transcriptional phenotypes could meaningfully limit the efficacy of monotherapies and fuel drug resistance, although to an unknown extent. To determine if transcriptional differences between tumor cells lead to differential drug responses we performed single cell RNA-seq on cell line and PDX models of breast cancer revealing cell subpopulations in states associated with resistance to standard-of-care therapies. We found that TNBC models contained a subpopulation in an inflamed cellular state, often also present in human breast cancer samples. Inflamed cells display evidence of heightened cGAS/STING signaling which we demonstrate is sufficient to cause tumor cell resistance to chemotherapy. Accordingly, inflamed cells were enriched in human tumors taken after neoadjuvant chemotherapy and associated with early recurrence, highlighting the potential for diverse tumor cell states to promote drug resistance.

FRP-XGBoost: Identification of ferroptosis-related proteins based on multi-view features

Ferroptosis represents a novel form of programmed cell death. Pan-cancer bioinformatics analysis indicates that identifying and modulating ferroptosis offer innovative approaches for preventing and treating diverse tumor pathologies. However, the precise detection of ferroptosis-related proteins via conventional wet-laboratory techniques remains a formidable challenge, largely due to the constraints of existing methodologies. These traditional approaches are not only labor-intensive but also financially burdensome. Consequently, there is an imperative need for the development of more sophisticated and efficient computational tools to facilitate the detection of these proteins. In this paper, we presented a XGBoost and multi-view features-based machine learning prediction method for predicting ferroptosis-related proteins, which was referred to as FRP-XGBoost. In this study, we explored four types of protein feature extraction methods and evaluated their effectiveness in predicting ferroptosis-related proteins using six of the most commonly used traditional classifiers. To enhance the representational power of the hybrid features, we employed a two-step feature selection technique to identify the optimal subset of features. Subsequently, we constructed a prediction model using the XGBoost algorithm. The FRP-XGBoost achieved an accuracy of 96.74 % in 10-fold cross-validation and a further accuracy of 91.52 % in an independent test. The implementation source code of FRP-XGBoost is available at https://github.com/linli5417/FRP-XGBoost.

Lysosome-targeting and legumain-triggered 68Ga-labeled probe for enhanced tumor PET imaging

Legumain is overexpressed in diverse tumors, serving as a significant tumor biomarker. Our study aimed to develop a new positron emission tomography (PET) probe [68Ga]Ga-NOTA-SF-AANM for imaging the expression level of legumain in vivo. The radio-labeling of [68Ga]Ga-NOTA-SF-AANM was accomplished within 15 min. The probe has good stability in vitro. NOTA-SF-AANM exhibited rapid response to recombinant human legumain enzyme, enabling intramolecular condensation cyclization. Cellular uptake and lysosomal co-localization experiments demonstrated that the probe was able to differentiate specifically between MDA-MB-468 and PC-3 cancer cells with varying degrees of legumain expression. PET imaging displayed a significant and persistent signal (3.59 ± 0.30 %ID/mL at 60 min) in MDA-MB-468 tumors, while PC-3 tumors exhibited lower radioactivity (1.08 ± 0.35 %ID/mL at 60 min), further validating the specific targeting of [68Ga]Ga-NOTA-SF-AANM towards legumain. [68Ga]Ga-NOTA-SF-AANM is a promising tool for precise diagnosis of legumain-related diseases due to its advantages in radio-labeling and accurate monitoring of legumain expression levels.

Efficient Generation of Murine Chimeric Antigen Receptor (CAR)-T Cells.

Engineered cell therapies utilizing chimeric antigen receptor (CAR)-T cells have achieved remarkable effectiveness in individuals with hematological malignancies and are presently undergoing development for the treatment of diverse solid tumors. So far, the preliminary evaluation of novel CAR-T cell products has predominantly taken place in xenograft tumor models using immunodeficient mice. This approach is chosen to facilitate the successful engraftment of human CAR-T cells in the experimental setting. However, syngeneic mouse models, in which tumors and CAR-T cells are derived from the same mouse strain, allow evaluation of new CAR technologies in the context of a functional immune system and comprehensive tumor microenvironment (TME). The protocol described here aims to streamline the process of mouse CAR-T cell generation by presenting standardized methods for retroviral transduction and ex vivo T cell culture. The methods described in this protocol can be applied to other CAR constructs beyond the ones used in this study to enable routine evaluation of new CAR technologies in immune-competent systems.

B7-H3 promotes proliferation and migration of lung cancer cells by modulating PI3K/AKT pathway via ENO1 activity.

B7-H3 (CD276) is overexpressed in diverse malignant tumors and plays critical roles in tumorigenesis and metastasis. However, the mechanism of B7-H3 in lung cancer remains unclear. This study aimed to explore the mechanism of interaction between B7-H3 and α-enolase (ENO1) in lung cancer progression. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) and Gene Expression Profiling Interactive Analysis 2 (GEPIA 2) databases were used to analyze the B7-H3 messenger RNA (mRNA) expression levels in lung cancer. The Kaplan-Meier (KM) plotter was used to analyze the correlation between B7-H3 and prognosis. Immunoprecipitation and glutathione S-transferase (GST) pull-down were used to verify the B7-H3 and ENO1 interaction. Cell counting kit-8 (CCK-8) and wound healing assays were used to investigate the effect of B7-H3 on the lung cancer growth. Based on the public databases, the analysis showed that B7-H3 mRNA expression levels were up-regulated and correlated with patient prognosis in lung cancer. By using B7-H3 gain and off cell model, we concluded that B7-H3 overexpression promoted proliferation and migration of SBC5 cells. Subsequently, we found that both B7-H3 and ENO1 knockdown could inhibit cell proliferation and migration, in the meanwhile, and the phosphorylation levels of PI3K-p85α, and AKT were significantly reduced. Interestingly, we determined that B7-H3 regulated ENO1 activity rather than changing its expression levels. Furthermore, we used an AP-III-a4 to block ENO1 activity in the experiments, which attenuated the roles of B7-H3 not only on phosphorylation levels of those molecules, but also on cell growth and migration. B7-H3 directly interacts with ENO1 in lung cancer cells. B7-H3 can promote proliferation and migration of lung cancer cells by modulating PI3K/AKT pathway via ENO1 activity.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types

BackgroundThe inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it...

Hepatitis B virus-related hepatocellular carcinoma exhibits distinct intratumoral microbiota and immune microenvironment signatures.

Emerging evidence supports a high prevalence of cancer type-specific microbiota residing within tumor tissues. The intratumoral microbiome in hepatocellular carcinoma (HCC), especially in viral (hepatitis B virus [HBV]/hepatitis C virus [HCV]) HCC, has not been well characterized for their existence, composition, distribution, and biological functions. We report herein a finding of specific microbial signature in viral HCC as compared to non-HBV/non-HCV (NBNC) HCC. However, the significantly diverse tumor microbiome was only observed in HBV-related HCC, and Cutibacterium was identified as the representative taxa biomarker. Biological function of the unique tumor microbiota in modulating tumor microenvironment (TME) was characterized by using formalin-fixed paraffin-embedded (FFPE) tissue-based multiplex immunofluorescence histochemistry (mIFH) allowing simultaneous in situ detection of the liver cancer cells surrounded with high/low density of microbiota, and the infiltrating immune cells. In HBV_HCC, the intratumoral microbiota are positively associated with increased tumor-infiltrating CD8+ T lymphocytes, but not the CD56+ NK cells. Two subtypes of myeloid-derived suppressor cells (MDSCs): monocytic MDSCs and polymorphonuclear MDSCs, were also found to be positively correlated with the intratumoral microbiota in HBV_HCC, indicating an inhibitory role of these microbial species in antitumor immunity and the contribution to the liver TME in combination of chronic viral hepatitis during HCC development.

Quantitative multiplex immunohistochemistry reveals inter-patient lymphovascular and immune heterogeneity in primary cutaneous melanoma.

Quantitative, multiplexed imaging is revealing complex spatial relationships between phenotypically diverse tumor infiltrating leukocyte populations and their prognostic implications. The underlying mechanisms and tissue structures that determine leukocyte distribution within and around tumor nests, however, remain poorly understood. While presumed players in metastatic dissemination, new preclinical data demonstrates that blood and lymphatic vessels (lymphovasculature) also dictate leukocyte trafficking within tumor microenvironments and thereby impact anti-tumor immunity. Here we interrogate these relationships in primary human cutaneous melanoma. We established a quantitative, multiplexed imaging platform to simultaneously detect immune infiltrates and tumor-associated vessels in formalin-fixed paraffin embedded patient samples. We performed a discovery, retrospective analysis of 28 treatment-naïve, primary cutaneous melanomas. Here we find that the lymphvasculature and immune infiltrate is heterogenous across patients in treatment naïve, primary melanoma. We categorized five lymphovascular subtypes that differ by functionality and morphology and mapped their localization in and around primary tumors. Interestingly, the localization of specific vessel subtypes, but not overall vessel density, significantly associated with the presence of lymphoid aggregates, regional progression, and intratumoral T cell infiltrates. We describe a quantitative platform to enable simultaneous lymphovascular and immune infiltrate analysis and map their spatial relationships in primary melanoma. Our data indicate that tumor-associated vessels exist in different states and that their localization may determine potential for metastasis or immune infiltration. This platform will support future efforts to map tumor-associated lymphovascular evolution across stage, assess its prognostic value, and stratify patients for adjuvant therapy.

Exploring non-invasive precision treatment in non-small cell lung cancer patients through deep learning radiomics across imaging features and molecular phenotypes

BackgroundAccurate prediction of tumor molecular alterations is vital for optimizing cancer treatment. Traditional tissue-based approaches encounter limitations due to invasiveness, heterogeneity, and molecular dynamic changes. We aim to develop and validate a deep learning radiomics framework to obtain imaging features that reflect various molecular changes, aiding first-line treatment decisions for cancer patients.MethodsWe conducted a retrospective study involving 508 NSCLC patients from three institutions, incorporating CT images and clinicopathologic data. Two radiomic scores and a deep network feature were constructed on three data sources in the 3D tumor region. Using these features, we developed and validated the ‘Deep-RadScore,’ a deep learning radiomics model to predict prognostic factors, gene mutations, and immune molecule expression levels.FindingsThe Deep-RadScore exhibits strong discrimination for tumor molecular features. In the independent test cohort, it achieved impressive AUCs: 0.889 for lymphovascular invasion, 0.903 for pleural invasion, 0.894 for T staging; 0.884 for EGFR and ALK, 0.896 for KRAS and PIK3CA, 0.889 for TP53, 0.895 for ROS1; and 0.893 for PD-1/PD-L1. Fusing features yielded optimal predictive power, surpassing any single imaging feature. Correlation and interpretability analyses confirmed the effectiveness of customized deep network features in capturing additional imaging phenotypes beyond known radiomic features.InterpretationThis proof-of-concept framework demonstrates that new biomarkers across imaging features and molecular phenotypes can be provided by fusing radiomic features and deep network features from multiple data sources. This holds the potential to offer valuable insights for radiological phenotyping in characterizing diverse tumor molecular alterations, thereby advancing the pursuit of non-invasive personalized treatment for NSCLC patients.